{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/victor/.local/lib/python3.6/site-packages/psycopg2/__init__.py:144: UserWarning: The psycopg2 wheel package will be renamed from release 2.8; in order to keep installing from binary please use \"pip install psycopg2-binary\" instead. For details see: <http://initd.org/psycopg/docs/install.html#binary-install-from-pypi>.\n",
      "  \"\"\")\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import datetime\n",
    "import time\n",
    "import matplotlib.pyplot as plt\n",
    "import math\n",
    "import psycopg2 as psql\n",
    "from psycopg2.extras import RealDictCursor\n",
    "import seaborn as sns\n",
    "sns.set(color_codes=True)\n",
    "\n",
    "import sys\n",
    "sys.path.append(\"..\")\n",
    "from tools.flight_projection import *\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "try:\n",
    "    conn = psql.connect(\"dbname='thesisdata' user='postgres' host='localhost' password='postgres'\")\n",
    "except Exception as e:\n",
    "    print(\"Unable to connect to the database.\")\n",
    "    print(e)\n",
    "\n",
    "cur_read = conn.cursor(cursor_factory=RealDictCursor)\n",
    "# cur_read.execute(\"SELECT * FROM public.ddr2_flights LIMIT 500;\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Visualization of DDR2 and ADS-B data sets</h2>\n",
    "The following code will plot the parsed DDR2 and ADS-B flights which have already been merged based on callsign and timestamp. Within the DDR2 flights there are both m1 and m3 files for respectively the planned and actual route. The ADS-B data is more granular. Interesting to see is that there are differences as well between DDR2-m3 and ADS-B"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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oaZqn59JR9ic2KQAAAADH7qpxqG3bv0zyXVd4738nefFxDwUAAADA6biWo+wBAAAAOOPEIQAAAIDCxCEAAACAwsQhAAAAgMKOcloZMKLW1reyvLqZ3vZOpqcms7gwm/m5ma7HAgAA4BSJQ1DU2vpWllY2srvXT5L0tneytLKRJAIRAABAIR4rg6KWVzcPwtC+3b1+llc3O5oIAACALohDUFRve2egdQAAAEaTOARFTU9NDrQOAADAaBKHoKjFhdlMjB/+K2BifCyLC7MdTQQAAEAXbEgNRe1vOu20MgAAgNrEIShsfm5GDAIAACjOY2UAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhY13PQAwmtbWt7K8upne9k6mpyazuDCb+bmZrscCAADgMuIQcOzW1reytLKR3b1+kqS3vZOllY0kEYgAAACGjMfKgGO3vLp5EIb27e71s7y62dFEAAAAXIk4BBy73vbOQOsAAAB0RxwCjt301ORA6wAAAHRHHAKO3eLCbCbGD//1MjE+lsWF2Y4mAgAA4EpsSA0cu/1Np51WBgAAMPzEIeBEzM/NiEEAAABngMfKAAAAAAoThwAAAAAKE4cAAAAAChOHAAAAAAoThwAAAAAKE4cAAAAAChOHAAAAAAoThwAAAAAKE4cAAAAAChOHAAAAAAoThwAAAAAKE4cAAAAAChvvegCA47S2vpXl1c30tncyPTWZxYXZzM/NdD0WAADA0BKHgJGxtr6VpZWN7O71kyS97Z0srWwkiUAEAABwBR4rA0bG8urmQRjat7vXz/LqZkcTAQAADD9xCBgZve2dgdYBAAAQh4ARMj01OdA6AAAA4hAwQhYXZjMxfvivtYnxsSwuzHY0EQAAwPCzITUwMvY3nXZaGQAAwNGJQ8BImZ+bEYMAAAAG4LEyAAAAgMLEIQAAAIDCxCEAAACAwsQhAAAAgMLEIQAAAIDCxCEAAACAwsQhAAAAgMLEIQAAAIDCxCEAAACAwsQhAAAAgMLEIQAAAIDCxCEAAACAwsQhAAAAgMLEIQAAAIDCxCEAAACAwsa7HgBg1Kytb2V5dTO97Z1MT01mcWE283MzXY8FAADwhMQhgGO0tr6VpZWN7O71kyS97Z0srWwkiUAEAAAMJY+VARyj5dXNgzC0b3evn+XVzY4mAgAAeHLiEMAx6m3vDLQOAADQNXEI4BhNT00OtA4AANA1cQjgGC0uzGZi/PBfrRPjY1lcmO1oIgAAgCdnQ2qAY7S/6bTTygAAgLNCHAI4ZvNzM2IQAABwZnisDAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBH2QMMmbX1rSyvbqa3vZPpqcksLsxmfm6m67EAAIARJQ4BDJG19a0srWxkd6+fJOlt72RpZSNJBCIAAOBEeKwMYIgsr24ehKF9u3v9LK9udjQRAAAw6sQhgCHS294ZaB0AAOBaiUMAQ2R6anKgdQAAgGslDgEMkcWF2UyMH/6reWJ8LIsLsx1NBAAAjDobUgMMkf1Np51WBgAAnBZxCGDIzM/NiEEAAMCp8VgZAAAAQGHiEAAAAEBh4hAAAABAYeIQAAAAQGHiEAAAAEBh4hAAAABAYeIQAAAAQGHiEAAAAEBh4hAAAABAYeIQAAAAQGHiEAAAAEBh4hAAAABAYeIQAAAAQGHiEAAAAEBh4hAAAABAYeIQAAAAQGHiEAAAAEBh4hAAAABAYeIQAAAAQGHiEAAAAEBh4hAAAABAYeIQAAAAQGHiEAAAAEBh4hAAAABAYeIQAAAAQGHjXQ8AwHBaW9/K8upmets7mZ6azOLCbObnZroeCwAAOGbiEACPs7a+laWVjezu9ZMkve2dLK1sJIlABAAAI8ZjZQA8zvLq5kEY2re718/y6mZHEwEAACdFHALgcXrbOwOtAwAAZ5c4BMDjTE9NDrQOAACcXeIQAI+zuDCbifHD/4uYGB/L4sJsRxMBAAAnxYbUADzO/qbTTisDAIDRJw4B8ITm52bEIAAAKMBjZQAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFjQ/y4aZp3p3kF5K8uG3bTzdN82NJfibJI0n2kvxM27afOPYpAQAAADgRR75zqGmalyR5eZLPXXo9neQXk/xA27Z3JHlPkg+dxJAAAAAAnIwjxaGmaSaTfCDJWx6zfO7SjxsvvX5mkr8+1ukAAAAAOFFHvXPoPUk+2rbthf2Ftm2/mOTfJvmzpmnuT/Ifk7z12CcEAAAA4MRcdc+hpmnmk3x3kndetj6V5N8leVnbtm3TND+U5HeapvnOtm0vHnWA6elnDDgyw+j8+Ruv/iHgVLkuYfi4LmH4uC5h+LguT99RNqReSPLCJPc1TZMk35Lk7jy6EfWX27Ztk6Rt2//RNM2vJ/nmJA8edYBe76H0+0duSQyh8+dvzIMPfrXrMYDHcF3C8HFdwvBxXcLwcV1eu7GxcwPfiHPVONS27fuSvG//ddM0F5L8YJLJJC9pmuYftW37t03TvCrJdpIvDjQBAAAAAJ0Z6Cj7x2rb9k+bpvnPSVabptlNspPktYM8UgYAAABAtwaOQ23bPv8xX78/yfuPcyAAAAAATs9RTysDAAAAYASJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhY13PQAAnLa19a0sr26mt72T6anJLC7MZn5upuuxAACgE+IQAKWsrW9laWUju3v9JElveydLKxtJIhABAFCSx8oAKGV5dfMgDO3b3etneXWzo4kAAKBb4hAApfS2dwZaBwCAUScOAVDK9NTkQOsAADDqxCEASllcmM3E+OH//U2Mj2VxYbajiQAAoFs2pAaglP1Np51WBgAAjxKHAChnfm5GDAIAgEs8VgYAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUJg4BAAAAFCYOAQAAABQmDgEAAAAUNj4IB9umubdSX4hyYvbtv100zTPTvKBJC9N8o0kv9W27XuOfUoAAAAATsSR41DTNC9J8vIkn3vM8q8n+YO2bX/k0mdmjnU6AAAAAE7UkR4ra5pmMo/eIfSWx6x9W5LvTPJf99fatt067gEBAAAAODlH3XPoPUk+2rbthcesfUeSv07yK03T/FnTNP+zaZq54x4QAAAAgJNz1cfKmqaZT/LdSd552VvX5dHHzH6ubdsfb5pmMcldSWYHGWB6+hmDfJwhdf78jV2PAFzGdQnDx3UJw8d1CcPHdXn6zl28ePFJP9A0zTuT/HSS3UtL35LkC3n0cbKfbNv2BY/57N8neV7btl88wu/9/CT39XoPpd9/8hkYbufP35gHH/xq12MAj+G6ZFSsrW9leXUzve2dTE9NZnFhNvNzZ3OLQ9clDB/XJQwf1+W1Gxs7t38jzq1JLhzl11z1zqG2bd+X5H37r5umuZDkB5OsJ3lj0zRzbduuN03zT5P8XZLeoIMDAFxubX0rSysb2d3rJ0l62ztZWtlIkjMbiAAAhtFR9xx6nLZtLyb5N0l+rWma/5vkPyVZvLQOAHBNllc3D8LQvt29fpZXNzuaCABgNB35KPt9bds+/zFf/58k33OcAwEAJI/eKTTIOgAAT81TvnMIAOAkTU9NDrQOAMBTIw4BAENpcWE2E+OHv1WZGB/L4sJAB6MCAHAVAz9WBgBwGvY3nR6V08oAAIaVOAQADK35uRkxCADghHmsDAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwG1IDAGfe2vqWU80AAJ4icQgAONPW1reytLKR3b1+kqS3vZOllY0kEYgAAI7AY2UAwJm2vLp5EIb27e71s7y62dFEAABnizgEAJxpve2dgdYBADhMHAIAzrTpqcmB1gEAOEwcAgDOtMWF2UyMH/6WZmJ8LIsLsx1NBABwttiQGgA40/Y3nXZaGQDAUyMOAQBn3vzcjBgEAPAUeawMAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMEfZAwBlra1vZXl1M73tnUxPTWZxYTbzczNdjwUAcKrEIQCgpLX1rSytbGR3r58k6W3vZGllI0kEIgCgFI+VAQAlLa9uHoShfbt7/SyvbnY0EQBAN8QhAKCk3vbOQOsAAKNKHAIASpqemhxoHQBgVIlDAEBJiwuzmRg//K3QxPhYFhdmO5oIAKAbNqQGAEra33TaaWUAQHXiEABQ1vzcjBgEAJTnsTIAAACAwsQhAAAAgMLEIQAAAIDCxCEAAACAwsQhAAAAgMLEIQAAAIDCxCEAAACAwsQhAAAAgMLEIQAAAIDCxCEAAACAwsQhAAAAgMLEIQAAAIDCxCEAAACAwsQhAAAAgMLEIQAAAIDCxCEAAACAwsQhAAAAgMLEIQAAAIDCxCEAAACAwsQhAAAAgMLEIQAAAIDCxCEAAACAwsQhAAAAgMLEIQAAAIDCxCEAAACAwsQhAAAAgMLEIQAAAIDCxCEAAACAwsQhAAAAgMLEIQAAAIDCxCEAAACAwsQhAAAAgMLEIQAAAIDCxCEAAACAwsQhAAAAgMLEIQAAAIDCxCEAAACAwsQhAAAAgMLGux4AAICrW1vfyvLqZnrbO5memsziwmzm52a6HgsAGAHiEADAkFtb38rSykZ29/pJkt72TpZWNpJEIAIArpnHygAAhtzy6uZBGNq3u9fP8upmRxMBAKNEHAIAGHK97Z2B1gEABiEOAQAMuempyYHWAQAGIQ4BAAy5xYXZTIwf/rZtYnwsiwuzHU0EAIwSG1IDAAy5/U2nnVYGAJwEcQgA4AyYn5sRgwCAE+GxMgAAAIDCxCEAAACAwjxWBgAwQtbWt+xNBAAMRBwCABgRa+tbWVrZyO5eP0nS297J0spGkghEAMAVeawMAGBELK9uHoShfbt7/SyvbnY0EQBwFohDAAAjore9M9A6AEAiDgEAjIzpqcmB1gEAEnEIAGBkLC7MZmL88Ld3E+NjWVyY7WgiAOAssCE1AMCI2N902mllAMAgxCEAgBEyPzcjBgEAA/FYGQAAAEBh4hAAAABAYeIQAAAAQGHiEAAAAEBh4hAAAABAYU4rAwAobG19K8urm+lt72R6ajLMdVLYAAAftElEQVSLC7NOOwOAYsQhAICi1ta3srSykd29fpKkt72TpZWNJBGIAKAQj5UBABS1vLp5EIb27e71s7y62dFEAEAXxCEAgKJ62zsDrQMAo0kcAgAoanpqcqB1AGA0iUMAAEUtLsxmYvzwt4MT42NZXJjtaCIAoAs2pAYAKGp/0+nLTytLknd88JNOMAOAIsQhAIDC5udmDoUfJ5gBQD0eKwMA4IATzACgHnEIAIADTjADgHrEIQAADjjBDADqEYcAADjgBDMAqMeG1AAAHLjSCWY2owaA0SUOAQBwyOUnmAEAo00cAgDgyNbWt9xVBAAjRhwCAOBI1ta3srSycXDUfW97J0srG0kiEAHAGWZDagAAjmR5dfMgDO3b3etneXWzo4kAgOMgDgEAcCS97Z2B1gGAs0EcAgDgSKanJgdaBwDOBnEIAIAjWVyYzcT44W8fJ8bHsrgw29FEAMBxsCE1AABHsr/ptNPKAGC0iEMAABzZ/NyMGAQAI8ZjZQAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhQ0Uh5qmeXfTNBebpnnRZeu/emn9Gcc7HgAAAAAn6chxqGmalyR5eZLPXbb+r5JcPOa5AAAAADgFR4pDTdNMJvlAkrdctj6d5N1J3n78owEAAABw0o5659B7kny0bdsLl61/IMm727b9yrFOBQAAAMCpGL/aB5qmmU/y3Uneedn6DyXZbdv2d69lgOlp2xSNgvPnb+x6BOAyrksYPq5LGD6uSxg+rsvTd+7ixSffLqhpmncm+ekku5eWviXJF5J8JclUkr1L6/84yf1J7mzb9jNH+L2fn+S+Xu+h9Pu2LDrLzp+/MQ8++NWuxwAew3UJw8d1CcPHdQnDx3V57cbGzu3fiHNrkgtH+TVXvXOobdv3JXnf/uumaS4k+cG2bT/92M81TXMxyVzbtg8deWIAAAAAOnXVOAQAAKdlbX0ry6ub6W3vZHpqMosLs5mfm+l6LAAYaQPHobZtn3+F9XPXPA0AAGWtrW9laWUju3v9JElveydLKxtJIhABwAk66mllAABwopZXNw/C0L7dvX6WVzc7mggAahCHAAAYCr3tnYHWAYDjIQ4BADAUpqcmB1oHAI6HOAQAwFBYXJjNxPjhb08nxseyuDDb0UQAUIPTygAAGAr7m047rQwATpc4BADA0JifmxGDAOCUeawMAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgsPGuBwAAgFH1kbs3snrvA+lfTMbOJQt33Jw3vvr2rscCgEPEIQAAOAEfuXsjH//zBw5e9y/m4LVABMAw8VgZAACcgNV7HxhoHQC6Ig4BAMAJ6F8cbB0AuiIOAQDACRg7N9g6AHRFHAIAgBOwcMfNA60DQFdsSA0AACdgf9Npp5UBMOzEIQAAOCFvfPXtYhAAQ89jZQAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwDw/9u7/1i77/uu4y/fXOyFJM66O69e6Y9kF/JJa4V2WSfireMyaawbamBcpkJE04gOwcrUCaFOTDDUMQREXSWkQUorlSIr7YrUcdUOJBMhtt3RzojSNWJ18YdiJe1K69a9qepmSmyce/njnuveWL72Ofa993uu34+HdOV7vvdc561EH93cp76fzxcAAAoThwAAAAAKE4cAAAAAChOHAAAAAAoThwAAAAAKE4cAAAAAChOHAAAAAAoThwAAAAAKE4cAAAAAChOHAAAAAAoThwAAAAAKE4cAAAAAChOHAAAAAAoThwAAAAAKE4cAAAAAChOHAAAAAAoThwAAAAAKE4cAAAAAChOHAAAAAAoThwAAAAAKE4cAAAAAChOHAAAAAAoThwAAAAAKE4cAAAAAChOHAAAAAAoThwAAAAAKm53kza21dyX55ST3JbmQ5P1JvjfJxSSfSvJ3eu/PbfOMAAAAAOyQse8caq3dn+SBJF8YXbqQ5O/13u9N8qeT/PEk79z2CQEAAADYMWPFodbagSSPJXn7xrXe+9O998+MPl9N8t+TvGonhgQAAABgZ4x759CvJPlQ7/3pK32xtXZrkrcl+c1tmgsAAACAXXDNM4daa0eTvD7JL27x9dkk/y7Jb/XeJ45Dc3O3T/otTKFDh+4YegTgMtYlTB/rEqaPdQnTx7rcfeMcSL2Q5NVJnmqtJcnLkzzRWvsbSf5Lkg8n+UaSn7+eAVZWns3q6tr1fCtT4tChO3L27LeGHgPYxLqE6WNdwvSxLmH6WJc3bmZm38Q34lwzDvXeH03y6Mbr1trTSd6U5HNJjiV5IcnP9N4VHgAAAIA9ZuynlV3BTyZ5S9Yfa//p1tqTrbXHtmcsAAAAAHbDONvKXqT3ftfo088m2bet0wAAAACwq27kziEAAAAA9jhxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDBxCAAAAKAwcQgAAACgsNmhBwAAALgejz9xKstPfjmra8nMvmThdS/Lw2+8d+ixAPYccQgAANhzHn/iVH77M1++9Hp1LZdeC0QAk7GtDAAA2HOWn/zyRNcB2Jo4BAAA7Dmra5NdB2Br4hAAALDnzOyb7DoAWxOHAACAPWfhdS+b6DoAW3MgNQAAsOdsHDrtaWUAN04cAgAA9qSH33ivGASwDWwrAwAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAobHboAQAAAPi2EyfPZGn5dFbOnc/cwQNZXJjP0SOHhx4LuImJQwAAAFPixMkzOXb8VC5cXE2SrJw7n2PHTyWJQATsGNvKAAAApsTS8ulLYWjDhYurWVo+PdBEQAXiEAAAwJRYOXd+ousA20EcAgAAmBJzBw9MdB1gO4hDAAAAU2JxYT77Z1/8a9r+2ZksLswPNBFQgQOpAQAApsTGodOeVgbsJnEIAABgihw9clgMAnaVbWUAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhc1O8ubW2ruS/HKS+3rvn22tPZDk/UluTfJ0krf03r+23UMCAAAAsDPGvnOotXZ/kgeSfGH0eibJh5L8XO/9niS/m+TRnRgSAAAAgJ0xVhxqrR1I8liSt2+6/ANJnu+9f2L0+n1J3ry94wEAAACwk8a9c+hXknyo9/70pmuvzOguoiTpvX89yUxr7bu2bzwAAAAAdtI1zxxqrR1N8vokv7gTA8zN3b4Tfy277NChO4YeAbiMdQnTx7qE6WNdwvSxLnffOAdSLyR5dZKnWmtJ8vIkTyT5tSSv2nhTa+27k6z23p+ZZICVlWezuro2ybcwZQ4duiNnz35r6DGATaxLmD7WJUwf6xKmj3V542Zm9k18I841t5X13h/tvb+s935X7/2uJF9K8sYkv5rk1tbaG0Zv/dkkH51sZAAAAACGNPbTyi7Xe19N8nCSf91a+3zW7zDaka1nAAAAAOyMcbaVvcjo7qGNz38vyX3bORAAAAAAu+e67xwCAAAAYO8ThwAAAAAKE4cAAAAAChOHAAAAAAoThwAAAAAKE4cAAAAAChOHAAAAAAoThwAAAAAKE4cAAAAAChOHAAAAAAoThwAAAAAKE4cAAAAAChOHAAAAAAoThwAAAAAKE4cAAAAAChOHAAAAAAoThwAAAAAKE4cAAAAAChOHAAAAAAoThwAAAAAKE4cAAAAAChOHAAAAAAoThwAAAAAKE4cAAAAAChOHAAAAAAqbHXoAAAAAOHHyTJaWT2fl3PnMHTyQxYX5HD1yeOixoARxCAAAgEGdOHkmx46fyoWLq0mSlXPnc+z4qSQRiGAX2FYGAADAoJaWT18KQxsuXFzN0vLpgSaCWsQhAAAABrVy7vxE14HtJQ4BAAAwqLmDBya6DmwvcQgAAIBBLS7MZ//si3893T87k8WF+YEmglocSA0AAMCgNg6d9rQyGIY4BAAAwOCOHjksBsFAbCsDAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKEwcAgAAAChMHAIAAAAoTBwCAAAAKGx2nDe11j6W5O4kq0meTfKO3vuTrbU3JfknSfaNPv5x731pp4YFAAAAYHuNe+fQI7331/bevz/Je5J8sLW2L8njSR7uvb8uycNJjrXW3I0EAAAAsEeMFXJ679/c9PLOrN9BlNGfd44+/84kX+m9rwYAAACAPWGsbWVJ0lr7QJIfz/r2sZ/ova+11t6c5OOttT9KckeSv7AzYwIAAACwE/atra1N9A2ttYeTPJTkLyb5T0ne1Xv/ZGvth5N8JMlreu/PjvFX3ZXkqcnGBQAAAGAMdyd5epw3ThyHkqS19lySP5fk3/beX7Pp+v9K8tbe+6fG+GvuSvLUysqzWV2dfAamx6FDd+Ts2W8NPQawiXUJ08e6hOljXcL0sS5v3MzMvszN3Z5MEIeueeZQa+321torNr1+MMkzSb6Y5OWttTa6/uokL01yeuLJAQAAABjEOGcO3Zbko62125K8kPUw9GDv/Suttbcn+Y3W2sYh1G/rvT+zQ7MCAAAAsM2uGYd6719N8sAWX/twkg9v91AAAAAA7I6xHmUPAAAAwM1p7EfZAwAAAGx24uSZLC2fzsq585k7eCCLC/M5euTw0GMxIXEIAAAAmNiJk2dy7PipXLi4fgzxyrnzOXb8VJIIRHuMbWUAAADAxJaWT18KQxsuXFzNv/mPn8uJk2cGmorrIQ4BAAAAE1s5d/6K11fXkmPHTwlEe4g4BAAAAExs7uCBLb/mDqK9RRwCAAAAJra4MJ/9s1tnBXcQ7R3iEAAAADCxo0cO55GfvDcz+7Z+z4WLq/n1/9x3byiuizgEAAAAXJejRw7nZ970mqveQfRHz7/g7qEpJw4BAAAA122cO4icPzTdxCEAAADghmzcQbQV5w9NN3EIAAAAuGFHjxzO7bfObvn1CxdXs7R8ehcnYlziEAAAALAtHvqxe656/tDKufO7OA3jEocAAACAbXGt84fmDh7Y3YEYy9b3ewEAAABM6OiRw0nWzxi6cHH10vX9szNZXJgfaiyuQhwCAAAAttVGIFpaPp2Vc+czd/BAFhfmL11nuohDAAAAwLY7euSwGLRHOHMIAAAAoDBxCAAAAKAwcQgAAACgMHEIAAAAoDAHUgMAAACDOXHyzKWnmh16ya35qTfc7SDrXSYOAQAAAIM4cfJMjh0/lQsXV5MkZ7/xXI4dP5UkAtEusq0MAAAAGMTS8ulLYWjDhYurWVo+PdBENYlDAAAAwCBWzp2f6Do7QxwCAAAABjF38MBE19kZzhwCAAAABrG4MP+iM4eSZP/sTBYX5l90UPXcwQNZXJh3DtEOEYcAAACAQWzEnsufVpbkRdFo5dx5B1XvIHEIAAAAGMzRI4cvBZ9Dh+7I2bPfyi+895NbHlQtDm0/cQgAAACYKlc7qPptj/6WbWbbzIHUAAAAwFS51oHUG9vMTpw8s0sT3dzEIQAAAGCqLC7MZ//s1ZPFxjYzbpxtZQAAAMBUufyg6q1c7WuMTxwCAAAAps7mg6p/4b2fvGIIutb2M8ZjWxkAAAAw1a60zWz/7EwWF+YHmujm4s4hAAAAYKpdvs3M08q2lzgEAAAATL3N28yu5cTJM0LSBMQhAAAA4KZx4uSZHDt+Khcurib59mPvkwhEW3DmEAAAAHDTWFo+fSkMbfDY+6sThwAAAICbxlaPt/fY+62JQwAAAMBNY6vH23vs/dbEIQAAAOCm4bH3k3MgNQAAAHDT8Nj7yYlDAAAAwE1lksfeY1sZAAAAQGniEAAAAEBh4hAAAABAYeIQAAAAQGHiEAAAAEBh4hAAAABAYeIQAAAAQGHiEAAAAEBh4hAAAABAYeIQAAAAQGHiEAAAAEBh4hAAAABAYeIQAAAAQGHiEAAAAEBh4hAAAABAYeIQAAAAQGHiEAAAAEBh4hAAAABAYeIQAAAAQGHiEAAAAEBh4hAAAABAYeIQAAAAQGHiEAAAAEBh4hAAAABAYeIQAAAAQGHiEAAAAEBh4hAAAABAYeIQAAAAQGHiEAAAAEBh4hAAAABAYeIQAAAAQGGzQw8AAAAAMJQTJ89kafl0Vs6dz9zBA1lcmM/RI4eHHmtXiUMAAABASSdOnsmx46dy4eJqkmTl3PkcO34qSUoFItvKAAAAgJKWlk9fCkMbLlxczdLy6YEmGoY4BAAAAJS0cu78RNdvVuIQAAAAUNLcwQMTXb9ZiUMAAABASYsL89k/++I0sn92JosL8wNNNAwHUgMAAAAlbRw67WllAAAAAEUdPXK4XAy6nG1lAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFiUMAAAAAhYlDAAAAAIWJQwAAAACFzY7zptbax5LcnWQ1ybNJ3tF7f7K19h1J/kWSH0vyfJITvfe/tVPDAgAAALC9xopDSR7pvX8zSVprfynJB5Pcn+TdWY9C9/Te11prL92ZMQEAAADYCWPFoY0wNHJnktXW2u1J3prk5b33tdH7vjrBP/uWJJmZ2TfBtzCt/HeE6WNdwvSxLmH6WJcwfazLG7Pp398t437PvrW1tbHe2Fr7QJIfT7IvyU9kPSwtjT5+NOvbzX6p9/6JMf/Zb0jyX8cdFAAAAICx/UiSsRrN2HFoQ2vt4SQPJfmlJJ9O8td777/eWvszSf5Dkj/Zez83xl91IMkPJvlKkhcmGgIAAACAK7klyfcm+VSS8+N8w8RxKElaa88luSvJl5Ls39hW1lr7XJK39t7/x8R/KQAAAAC77pqPsm+t3d5ae8Wm1w8meSbJ15L8dpI/P7p+T5LvSfJ/dmZUAAAAALbbNe8cGj2B7ONJbsv69q9nkryz9/77rbXvy/qTy+aS/L8k/7D3fnxnRwYAAABgu1zXtjIAAAAAbg7X3FYGAAAAwM1LHAIAAAAoTBwCAAAAKEwcAgAAAChsdugB2Dtaa+9J8leS3JXkvt77Z0fX70lyLOtPrVtJ8tbe++eHmhMqucq6fDrJ86OPJPn7vfcnBhgRymmtzSV5PMl8kgtJPp/kb/fez7bWHkjy/iS3Jnk6yVt6718balao4hrrci3JHyRZHb394d77HwwzKdTRWvtYkruzvvaeTfKO3vuTfr8chjuHmMTHkvzZJF+47Pr7kjzWe78nyWNZ/59eYHdstS6T5Kd7768bfQhDsHvWkry799567/clOZ3k0dbaTJIPJfm50c/M303y6IBzQiVXXJebvv5Dm35mCkOwOx7pvb+29/79Sd6T5IOj636/HIA4xNh675/ovf/h5mutte9Jcn+Sj4wufSTJ/a21Q7s9H1R0pXUJDKv3/kzv/Xc2XfpvSV6V5AeSPN97/8To+vuSvHmXx4OSrrIugYH03r+56eWdSVb9fjkccYgb9Yok/7f3/kKSjP788ug6MKwPt9b+Z2vtva217xx6GKhodLfQ25P8ZpJXZtNdfr33ryeZaa1910DjQUmXrcsNv9Nae7K19s9bawcGGg3Kaa19oLX2xST/NMkj8fvlYMQhgJvTj/TeX5vkB5PsS/KvBp4HqvqXWT9HwRqE6XH5unxl7/31Wd+m/Zok/2iowaCa3vvf7L2/Msk/SPKrQ89TmTjEjfrDJH+itXZLkoz+fNnoOjCQja1mvffzSd6b5IeHnQjqGR0Y/6eS/NXe+2qSL2bTNpbW2ncnWe29PzPQiFDOFdbl5p+Z55J8IH5mwq7rvT+e5EeTfCl+vxyEOMQNGT1h5ckkD40uPZTkM733s8NNBbW11m5rrd05+nxfkr+W9XUK7JLW2j/L+hlDPzWKtEny6SS3ttbeMHr9s0k+OsR8UNGV1mVr7SWttVtHn88m+en4mQk7rrV2e2vtFZteP5jkmSR+vxzIvrW1taFnYI9orf1aksUkh5N8PclK7/1Ia+3erD9q8CVJvpH1Rw324SaFOq60LpM8mOTfJ7ll9PG5JD/fe//KUHNCJa21I0k+m+R/J3ludPmp3vtfbq39UNafuvId+faj7L86yKBQyFbrMsm7s74m15L8sSS/l+Tv9t6fHWJOqKK19tIkH09yW5IXsh6G3tl7/32/Xw5DHAIAAAAozLYyAAAAgMLEIQAAAIDCxCEAAACAwsQhAAAAgMLEIQAAAIDCxCEAAACAwsQhAAAAgMLEIQAAAIDC/j8bMSDDDDFV3wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cur_read.execute(\"select * from public.adsb_ddr2m3_flights limit 10;\")\n",
    "\n",
    "\n",
    "# lat_bounds = [49, 56]\n",
    "# lon_bounds = [1, 8]\n",
    "\n",
    "for dm1 in cur_read.fetchall():\n",
    "    \n",
    "    try:\n",
    "#         print(dm1['callsign'])\n",
    "        plt.figure(figsize=(20,20))\n",
    "#         print(dm1)\n",
    "#         a = pd.DataFrame(x['adsb'])\n",
    "#         dm1 = pd.DataFrame(x['ddr2_m1'])\n",
    "#         dm3 = pd.DataFrame(x['ddr2_m3'])\n",
    "        plt.scatter(list(dm1['lon']),list(dm1['lat']), c=\"b\", s=2)\n",
    "        plt.scatter(list(dm1['lon_seg_b']),list(dm1['lat_seg_b']))\n",
    "#         plt.scatter(list(dm3['lon_seg_b']),list(dm3['lat_seg_b']), c=\"g\", s=3)\n",
    "#         plt.scatter(list(a['lon']),list(a['lat']), c=\"b\", s=3)\n",
    "\n",
    "    except:\n",
    "        print('failed')\n",
    "\n",
    "# plt.xlim(tuple(lon_bounds))\n",
    "# plt.ylim(tuple(lat_bounds))\n",
    "plt.show()\n",
    "cur_read.close()\n",
    "conn.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=(30,30))\n",
    "lat_bounds = [51, 53.5]\n",
    "lon_bounds = [2, 6]\n",
    "\n",
    "for x in col_combi.find({})[:30]:\n",
    "    try:\n",
    "        a = pd.DataFrame(x['adsb'])\n",
    "        dm1 = pd.DataFrame(x['ddr2_m1'])\n",
    "        dm3 = pd.DataFrame(x['ddr2_m3'])\n",
    "        plt.scatter(list(dm1['lon_seg_b']),list(dm1['lat_seg_b']), c=\"r\", s=3)\n",
    "        plt.scatter(list(dm3['lon_seg_b']),list(dm3['lat_seg_b']), c=\"g\", s=3)\n",
    "        plt.scatter(list(a['lon']),list(a['lat']), c=\"b\", s=3)\n",
    "        plt.xlim(tuple(lon_bounds))\n",
    "        plt.ylim(tuple(lat_bounds))\n",
    "    except:\n",
    "        continue\n",
    "\n",
    "    \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Visualization of CTE over look ahead time for planned route</h2>\n",
    "The calculated CTE between the DDR2-m1 data and ADS-B data is plotted against the look-ahead time. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Anomalous value\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Anomalous value\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Anomalous value\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "math domain error\n",
      "math domain error\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
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      "math domain error\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Anomalous value\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Anomalous value\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Anomalous value\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Anomalous value\n",
      "Anomalous value\n",
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      "Anomalous value\n",
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      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
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      "Anomalous value\n",
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      "Anomalous value\n",
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      "Anomalous value\n",
      "Anomalous value\n",
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      "Anomalous value\n",
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      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
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      "Anomalous value\n",
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      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
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      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
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      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
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      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
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      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n",
      "Anomalous value\n"
     ]
    },
    {
     "ename": "ValueError",
     "evalue": "Columns must be same length as key",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-3-a5857f12417f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     37\u001b[0m         \u001b[0;32mcontinue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     38\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 39\u001b[0;31m     \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'curr_lat'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'curr_lon'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'curr_wp'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mSeries\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     40\u001b[0m     \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'next_lat'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'next_lon'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'next_wp'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mSeries\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     41\u001b[0m     \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'last_lat'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'last_lon'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'last_wp'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mSeries\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__setitem__\u001b[0;34m(self, key, value)\u001b[0m\n\u001b[1;32m   3114\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_setitem_frame\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3115\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mSeries\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndarray\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mIndex\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3116\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_setitem_array\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3117\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3118\u001b[0m             \u001b[0;31m# set column\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_setitem_array\u001b[0;34m(self, key, value)\u001b[0m\n\u001b[1;32m   3136\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mDataFrame\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3137\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3138\u001b[0;31m                     \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Columns must be same length as key'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3139\u001b[0m                 \u001b[0;32mfor\u001b[0m \u001b[0mk1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mk2\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3140\u001b[0m                     \u001b[0mself\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: Columns must be same length as key"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 2160x720 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "try:\n",
    "    conn = psql.connect(\"dbname='thesisdata' user='postgres' host='localhost' password='postgres'\")\n",
    "except Exception as e:\n",
    "    print(\"Unable to connect to the database.\")\n",
    "    print(e)\n",
    "\n",
    "max_inserts = 100\n",
    "fetch_batch_size = max_inserts\n",
    "cnt = 0\n",
    "\n",
    "cur_read = conn.cursor(cursor_factory=RealDictCursor)\n",
    "\n",
    "cur_read.execute(\"select * from public.adsb_ddr2m3_flights limit 5000;\")\n",
    "\n",
    "proj_dct = {}\n",
    "plt.figure(figsize=(30,10))\n",
    "bin_cte = []\n",
    "bin_dp_df = {}\n",
    "la_time = 1200\n",
    "bin_sec = 20\n",
    "\n",
    "for x in cur_read.fetchall():\n",
    "    \n",
    "    dc = {k: x[k] for k in ['ep_seg_b','lat_seg_b', 'lon_seg_b']}\n",
    "    ac = {k: x[k] for k in ['ts','lat','lon']}\n",
    "    \n",
    "    dc = pd.DataFrame.from_dict(dc)\n",
    "    ac = pd.DataFrame.from_dict(ac)\n",
    "\n",
    "    dc['wps'] = list(zip(dc.lat_seg_b, dc.lon_seg_b))\n",
    "    try:\n",
    "        df = add_waypoints_free(ac, dc['wps'])\n",
    "    except Exception as e:\n",
    "        print(e)\n",
    "        continue\n",
    "\n",
    "    df[['curr_lat', 'curr_lon']] = df['curr_wp'].apply(pd.Series)\n",
    "    df[['next_lat', 'next_lon']] = df['next_wp'].apply(pd.Series)\n",
    "    df[['last_lat', 'last_lon']] = df['last_wp'].apply(pd.Series)\n",
    "    \n",
    "    cte_arr = []\n",
    "    ate_arr = []\n",
    "    tte_arr = []\n",
    "\n",
    "    fl_dd = pd.DataFrame()\n",
    "\n",
    "    for ii, r in df.iterrows():\n",
    "#         print(r)\n",
    "        cte, ate, tte = calc_track_errors(r['last_wp'], r['curr_wp'], r['wp_ac'])\n",
    "        cte_arr.append(cte)\n",
    "        ate_arr.append(ate)\n",
    "        tte_arr.append(tte)\n",
    "\n",
    "\n",
    "    fl_dd['cte'] = cte_arr\n",
    "    fl_dd['ate'] = ate_arr\n",
    "    fl_dd['tte'] = tte_arr\n",
    "    fl_dd['time_proj'] = df['ts'] - df['ts'].min()\n",
    "    \n",
    "    for b in range(int(la_time/bin_sec)):\n",
    "        bmin = b*bin_sec\n",
    "        bmax = (b+1)*bin_sec\n",
    "        if str(bmax)+'_cte' not in list(bin_dp_df.keys()):\n",
    "            bin_dp_df[str(bmax)+'_cte'] = []\n",
    "            \n",
    "        bin_dp_df[str(bmax)+'_cte'].extend(fl_dd['cte'][(fl_dd['time_proj'] >= bmin) & (fl_dd['time_proj'] <= bmax)])\n",
    "    \n",
    "    bin_cte.extend(cte_arr)\n",
    "    \n",
    "#     plt.figure(figsize=(30,30))\n",
    "#     plt.scatter(df['curr_lat'],df['curr_lon'], c='g')\n",
    "#     plt.scatter(df['lat'], df['lon'],c='b')\n",
    "#     plt.scatter(fl_dd['time_proj'],fl_dd['cte'],s=2, c='b')\n",
    "# plt.ylim((-100000,100000))\n",
    "# plt.xlim((0,1200))    \n",
    "# plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following boxplot shows the distribution of the CTE between the m1 data and ADS-B data in bins of 20 seconds for a look-ahead time up to 3000 seconds from the start of the flight. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create bin dataframe\n",
    "box_data = []\n",
    "bin_df = bin_dp_df\n",
    "\n",
    "for k in bin_df.keys():\n",
    "    if '_cte' in k:\n",
    "        box_data.append((int(k.strip('_cte')), [i for i in bin_df[k] if not np.isnan(i)]))\n",
    "    \n",
    "box_data_sort = sorted(box_data, key=lambda tup: tup[0])\n",
    "box_data_2 = [i[1] for i in box_data_sort]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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72c/mG9/4Rj760Y9m+PDhOfnkk/Pggw923PfKK6/M3/7t32a//fZLS0tLPv3pT+eNN95Y788ZOXJkjjrqqBx22GFZvXp1p3XPNsfhhx+eN998M1//+tczb968bLvttjnggANy5JFHblFdAGhETe21jOkGAAAAgBIyLREAAACAyhJuAQAAAFBZwi0AAAAAKku4BQAAAEBlCbcAAAAAqCzhFgAAAACV1benG6iy119/M2vWtG9RjSFDBmXJkuWF9FNULT3Vt06RtcpWp8haeqpvnSJrla1OkbX0VN86RdYqW50ia+mpvnWKrFW2OkXW0lN96xRZq2x1iqylp/rWKbJW2eoUWavRe9qY5uambLfdNpt8P+HWFlizpn2Lw621dYpSVC091bdOkbXKVqfIWnqqb50ia5WtTpG19FTfOkXWKludImvpqb51iqxVtjpF1tJTfesUWatsdYqspaf61imyVtnqFFmr0XvqDqYlAgAAAFBZwi0AAAAAKku4BQAAAEBlCbcAAAAAqCzhFgAAAACVJdwCAAAAoLKEWwAAAABUlnALAAAAgMoSbgEAAABQWcItAAAAACpLuAUAAABAZQm3AAAAAKgs4RYAAAAAlSXcAgAAAKCyhFsAAAAAVJZwCwAAAIDK6tvTDQAAAABUUVvb+Myd+3zH5ZEj98i0adN7sKPeSbgFAAAAsBnWBlktLaMyZ85zPdxN72VaIgAAAACVZeQWADSA9w6JTwyLBwCgdxBuAUADMCQeAIDeyrREAAAAACpLuAUAAABAZQm3AAAAAKgs4RYAAAAAlWVBeQDoIc5wCAAAW064BQA9ZN0Qy1kOAQBg85iWCAAAAEBlCbcAAAAAqCzhFgAAAACVZc0tAAAAgB7kRENbRrgFAJvImw8AAIq09n2kkwxtHuEWAGwibz4AAKA8rLkFAAAAQGUZuQUAAADQIN67hEZvWD5DuAUAAADQIHrjEhqmJQIAAABQWcItAAAAACpLuAUAAABAZQm3AAAAAKgsC8oDAAAAvcZ7zyaY9I4zCjYy4RYAAADQa/TGswk2OtMSAQAAAKgs4RYAAAAAlSXcAgAAAKCyShNuvf766znttNNyxBFHZPz48TnjjDPy2muvJUnmzJmTo48+OkcccUT+5m/+JkuWLOm4X3dsAwAAAKAaShNuNTU15dRTT83999+f6dOnZ9ddd80VV1yRNWvW5Kyzzsr555+f+++/P62trbniiiuSpFu2AUBv1tY2Pi0to9LSMio777xzWlpGpa1tfE+3BQAAG1SacGvw4MHZb7/9Oi63tLRk/vz5+e1vf5sBAwaktbU1SXL88cfnvvvuS5Ju2QYAvdm0adMzZ85zHWcOmjPnOafFBgCg1EoTbq1rzZo1+fGPf5xDDz00CxYsyE477dSxbfvtt8+aNWuydOnSbtkGAAAAQHX07ekG1ueCCy7IwIEDc+KJJ+aBBx7o6XY2aMiQQYXUGTZs20LqFFlLT/WtU2StstUpspae6lunyFplq1NkLT3Vt06RtcpWp8haeqpvnSJrla1OkbX0VN86RdYqW50ia+mpvnWKrFW2OkXWavSeukPpwq1LL700L7/8cqZMmZLm5uaMGDEi8+fP79j+2muvpbm5OYMHD+6WbZtiyZLlWbOmfQse7bs7yKuvLtuiGkXX0lN96xRZq2x1iqylp/rWKbJW2eoUXauoOkXWKltPZXztylanyFp6qm+dImuVrU6RtfRU3zpF1ipbnSJr6am+dYqs5b1cfWsV+XxvTHNz02YNJCrVtMTvfve7+e1vf5trrrkm/fv3T5LsvffeWblyZWbPnp0kufXWWzN27Nhu2wYAAABV1Ognhln7+BrxsbFlSjNy6/nnn891112X3XbbLccff3ySZJdddsk111yTyy67LN/61rfyhz/8ITvvvHMuv/zyJElzc3Ph2wAAAKCK1j0JTEvLqI4TxPSktrbxmTv3+U7XjRy5x2adsGbtfcry2CiP0oRbe+yxR/793/99vds+/OEPZ/r09e/43bENAAAA2HJlDNxoPKUJtwAAAKBK3jsqaXNHJBU5ugnKph77t3ALAOgWRb3hB4CyKmqanOl2NLJ6jN4TbgEA3cIbdQCA6qrSiELhFgAAANCJEdhU6YtK4RYAAADQSZWCDWju6QYAAAAAYHMZuQX0ClWaLw4AAEDthFtAr1CPM3QAAABQf6YlAgAAAFBZwi0AAAAAKku4BQAAAEBlCbcAAAAAqCwLygMAbCJnYAUAKA/hFgDQa7w3lNrcQGrtfZx9FQCg5wm3AIBeo5FDKaPJAIDeSrgFANAAGjm4AwDoinALAKAHFTVVEgCgtxJuAQD0ICOuAAC2THNPNwAAAAAAm8vILQAAALqFk10A9SDcAgAAoFuYeg3Ug2mJAAAAAFSWkVsAQKmZ0gIAQFeEWwD0Gu8NSQQk1bDua2RaCwAA7yXcgk3kwzFUl3U/AACg8Qi3YBP5cAwAUF2mOgM0HuEWAADQa/iiEqDxOFsiAAAAAJVl5BYAAMAmMr0RoDyEWwAAAJvImVwBysO0RAAAAAAqS7gFAAAAQGWZlggN4L1rPljvAQAAgN5CuAUNwCmtAQAA6K2EW0AHZ/0BAACgaoRbQAcjwADwRQdUl99foLcSbgEA0GHdD8G+7ID6KGr91CJ/f63pClSJcAt6iG/WAKA2/mbS6Mo4er6MPRXFMQUaj3ALekijfzPu2z4AivoA2eh/M9k4YQRFauTgDnor4RbQLbxpAMDfgvpq5ABIwAlAV4RbAADQg4peb0n4Q6MyMwDYEOEWAAD0IKEU1MbvCrAhzT3dAAAAAABsLiO3gFJr5PVDAKCsTP8CqI/D/r+Ds3jRK52ua2kZ1eny0OE75sGZv6hjV9Uj3KJXEJBUl+HnAFB//v4C1MfiRa/kw8df2+Vtfn3rpDp1U13CLXoFZ9ihjIoMXX3DDlBfvjirjecJaETrG22VGHHVk4RbAD2kyNC1jN+wC9yAMir6zIRJuY69ZVPGv08AW6qW0VaJEVf1JNwCoFsU9YHGt/5AkYQtADSiWkaTNfJIMuEWAKXmgygAAHStt6/d1dzTDQAAAADA5jJyiw6m/gAAAFRPkVPS1lfLQum9S1H7QD2nSgq3ekgZgyRTfwAAaFQ+sNPIipySVrbpbUWemdBxoDZF7QP13JeEWz1EkFQbZ1ujjMoYTgMAXSvbB3agNkWemdBxoHEJtyg1ISBlZL/svRr5277efoYdoJwa/dhUxak/eL5r5XminoRbDcDoJoD6KOrbvjK+2fNNZm0aOeCEMirjsanIY3jZpv40+vSvonoqcr8s4/NUlDL+/tK4hFsNwCgSoCimXNaHN3vV1civXRlDV6rLB/ZqHgfKOP2ryMCtjK9dGXuCKhJuAdBh3RBLYA7dp4yjI3zAqq8y7gNFsj9RlCIDN6BxCbconJEfAPVTxg+1ZVNkiFCUMo6OoL7sAwBQHOEWhTPyA6B+yvahtrtHo7y3VlEjkhIf/otkkexqKmMQDAC1EG4B0NB8OK4vo1FIyrdIdpEa+ZgiCAagqoRbADS0Mn44BurP2mQA0LiEW5SSNWQoShm/YS9jTwCNTigFAI1LuFVnQpva1PPUwVUNNhr9LEtFKeOHmTL2BAAAUFXCrTpr5A+1ZQyS6hmSJfWdzmBdm/pr5BCwjDzfAABALYRbFKaRAxILrNamjAFnkcq2jzf6Wa3K9nwDAADl1KvDrRdffDHnnHNOli5dmsGDB+fSSy/Nbrvt1tNt1aTRQwSqqcgwwqidjRO6AgAASfKj4/bJ7tvf1OVtXjhunzp1U3+9Otz61re+lb/+67/OMccck7vuuivnn39+brqp652hLIxooNHZx6up0UeTAQBAkYoKpT572282/vnptkmZ83eb1F5l9Npwa8mSJfnd736XG264IUkybty4XHDBBXnttdey/fbb93B3ANXU6KPJevs3YgD1VuRx1zEcKKMyhlJFHS/redztteHWggULssMOO6RPnz5Jkj59+mT48OFZsGBBrwu3Gnn6lzcxUJtGnupc5HGgqDcfjk31VcvznXjOy8jvSnWVcSRCGY/hVfwAWW9FHsPL+HyXsSc2rtHfWxR1vKxncNdrw60iDBkyaJPvU+tBZ9iwbetSJ0muPGR4dh+yW9e1lqyoa09F1ar1l2ned7f8sdXaUz33gTL2VO99oJF7KnIfqOdxoNaeynYc2BT17KmR98t67gNJcX8Pqvo8lfF46Xeluj3V+9hby35ZVK0iH1tRtRr5PW+Rx/CyPd9l7cnxsr77Za2KOs7V83hZzzq9NtwaMWJEFi5cmNWrV6dPnz5ZvXp1Fi1alBEjRtRcY8mS5Vmzpn2Tfm7tyeWyutRp9J5q9eqrW/7Yau2pns93GXuyX9oH6t1TrTZ2HOiJWrXUsV8Wtw8kxfw9qOrzVMbjZa38rpSvp1rV83hZ71pV7KmM++WmKNtrV8V9IHG8tF/Wv9a6dZqbmzZrIFFzIZ1U0JAhQ7LXXnvl5z//eZLk5z//efbaa69eNyURAAAAoMp67citJPn2t7+dc845J9dee23e97735dJLL+3plgAAAADYBL063Bo5cmR++tOf9nQbm2Xo8B03eraxocN3rFM3QE+o5Tiw9nYAAACNqleHW1W2vjOWtbSMypw5z9W/GWCTFBVOl/E4IHADAADqTbgFUKPeHkrV+7E18gjVRn5skNjHKW4fKHJfsl8CNC7hVp2V8Y9qGXuCohS5f783uOnpQKpIZQzcinq+y3iMK+PzDUVq5OMltSlqHyjyeGm/BGhcwq06K+Mf1Ub+AAlCBOwDUF3eW9SXqeUAVJVwi8L4AAk0Oh+066ue05qKrFXVnsqojO8tPN8AUD7CLaCh36hDkco4+rZsigxtivqgXcZpTWXsidoU9doJOAGgOMItqKju/ADpgxFUR9kWbTbyo7oEJPUl4KwuvysA5SPcgooq4wdIZzSC+ivjSCKqyT4AtXFmYIDyEW4BhfEtNABA7bzfoSiC0uoq42tXxp42RrgFNbAuBgAAUFZG31ZXGUPuMva0McItqEF3jkjakloAQG18uUQjs38DvZ1wCwCAhlfFb6GhVr48rS7BJI2snvu3cAsAAIBCl+KgNoJ3Glk9g3fhFgAA0C3a2sZn7tznk7z7gSZJRo7cI9OmTe/JttgAI8Cgunr7KEDhFgAA0C3WhljDhm2bV19d1sPdUEVlHE3W20MEyqm3h9PCLRqaPzwAANW37giw5N0PbEaAlVtR78OL/MBexp7YuDKeub6MoWtvJ9zqIYZo14c/PAAA1bfue2SjwKqhjGtJlbEnNq47z1xfVJ0tqUUxhFs9xBBtgPp77xcLvlQAAIDqE24B0GsU9cWC0bcAAFAewi2ATSTYwOhbimREIQBlYt1iqki4RSk5oFJmgo3a+MAOtXFMAaBMrE1GFQm3KCUHVKg+UwABAIB6EG41AKMjgEZmVAsAANAV4VYD8MEPoJrW/XIi8QUFAABsDuEWQA8RbLDua+0LCgAA2DzCLYAeItgAgPqzliNA4xFuAQAAvYYlPQAaj3ALAAAAKNTQ4Tvm17dO2uhtoAjCLQAAAKBQD878xR9d19IyKnPmPFf/Zmh4zT3dAPRWbW3j09IyqmOth5aWUWlrG9/DXVFVa/enxL4EAAD0LkZu0cHimvXV6IuJv3d/si91L+uHAAAAvZVwiw5FfTheN9RIBBu9VXfsT0JXAAAA3ku4ReEafUQS9WVEEgAAAF0RbgFAAzDKsb483wAA5SHcAoAGYJRjfZXx+Ra4AQC9lXALAKABlDFwAwCoh+aebgAAAAAANpdwCwAAAIDKMi0R6GC9FgAAAKpGuEWpvTdsEbR0L+u1AAAAUDXCLUpN2AIAAAB0xZpbAEC3aGsb3zHFuaVlVNraxvdwRwAANCIjtwCAbmH0LQAA9WDkFgAAAACVZeQWAFBq655cJHGCEQAAOhNuAQCltm6IZYojAADvVdO0xBtuuCHPPvtskmTOnDk5+OCDc+ihh+app57q1uYAAAAAoCs1hVs33nhjdtlllyTJlVdemc997nP5whe+kIsuuqhbmwMA6mvtGQ6d5RAAgKqoaVrismXLsu2222b58uX593//99zQYLfCAAAgAElEQVR4443p06dPLr300u7uD4A6srYRpgACSee/B/4WAFB2NYVbI0aMyK9//ev83//7f9Pa2po+ffpk+fLl6dOnT3f3B0AdCTYASP7r74G/BQBUQU3h1tlnn50vf/nL6d+/f66++uokyaxZs/KhD32oW5sDACiS0SgAAI1no+HWmjVr0r9//zz88MPp379/x/Vjx47N2LFju7U5AIAiGY0CANB4NrqgfHNzcyZNmtQp2EqSfv36pV+/ft3WGAAAAABsTE1nSxwzZkzmzJnT3b0AAAAAwCapac2tnXbaKaeddlo++clPZscdd0xTU1PHtq985Svd1hwAAAAAdKWmcOsPf/hDDjvssCTJwoULu7UhAABg0733hAlJnDQBgF6hpnDr4osv7u4+AACALeCECQAUqUpfmtQUbiXJ3Llzc99992XJkiU5//zz88ILL2TVqlUZNWpUd/YHAEBFVelNMQDQWZW+NKlpQfkZM2bkhBNOyMKFC3PnnXcmSd58881ccskl3docAADVNW3a9MyZ81zmzZuXOXOey5w5zwm2AIDC1TRy6+qrr86NN96YUaNGZcaMGUmSUaNG5bnnnuvW5gAAAACgKzWFW6+99lr23HPPJOk4U2JTU1OnsyYCAEB3WHd6Y/LuFEfTGwGAtWoKtz74wQ/mrrvuyqc//emO6+65557ss88+3dYYAAD1V8Ygad2fXYV1PwCA+qop3DrvvPNyyimn5Pbbb8+KFStyyimn5MUXX8zUqVO7uz8AAOpIkAQAVE1N4dbIkSMzY8aMzJo1KwcffHBGjBiRgw8+ONtss0139wcAAAAAG1TT2RIvvPDCbL311vnUpz6VU089NUcddVS22Wab/MM//EN39wdQiLa28WlpGdVxKvqWllFpaxvfw10BUFX+rgBAedQ0cutnP/tZvvnNb/7R9XfffXfOO++8wpsCKJppNgAUyd8Vyrg+HUAZ1eN42WW4dfvttydJVq9e3fH/tX7/+99n8ODBhTTxne98J0888UT69++fgQMH5rzzzsuHPvShJMnixYtz9tlnZ968eRkwYEAuuOCC7Lvvvt22jcbkzQcAAEUqMuBc972q96lAo6nH8azLcOuuu+5Kkrz99tsd/0+SpqamDB06NJdeemkhTXziE5/Iueeem379+mXWrFn52te+lgcffDBJcuWVV6a1tTVTp07N7Nmzc9ZZZ+X+++9PU1NTt2yjMfl2FQCAslr7XtX7VIDN02W4dfPNNydJrrrqqnzta1/rtiYOOeSQjv+3tLTklVdeyZo1a9Lc3Jz77rsvDz30UJKktbU1/fv3zzPPPJN99tmnW7YBAAAAUB01rbn1ta99La+//noeeeSRLF68OKeeemoWLlyY9vb27LjjjoU2dMstt+Tggw9Oc3NzXn/99bS3t2f77bfv2D5ixIi88sor2XXXXQvftqnh1pAhg7bgkf6XYcO2LaROkbX0VN86RdYqW50ia+mpvnWKrFW2OkXW0lN96xRZq2x1iqylp/rWKbJW2eoUWUtP9a1TZK2y1Smylp7qW6fIWmWrU2StRu+pO9QUbv3rv/5rvvSlL2XvvffOr3/965x66ql5+eWXM3Xq1EyZMmWj9z/22GMzf/789W57/PHH06dPnyTJPffck+nTp+eWW27ZhIfQc5YsWZ41a9q3qEaRQ4+LqqWn2jVqT2V8vvVU3zpF1ipbnSJr6am+dYqsVbY6RdbSU+3K0tO66y3tvPPOW7zeUhmfbz3Vt85aZftdaeTHVmQtPVWzTpG1ytZTPadMNzc3bdZAoprCrYsuuij/+I//mP333z9jxoxJkuy77775zW9+U9MPueOOOzZ6mwceeCBXXXVVbrzxxgwdOjRJst122yVJXnvttY6RVgsWLMiOO+7YLdsAAKDerLcEAFumuZYbzZs3L/vvv3+SdCy63q9fv6xevbqQJmbNmpWLL744119/fXbZZZdO28aOHZtbb701STJ79uysXLkye++9d7dtAwAAAKA6ahq5NXLkyDz22GM58MADO657/PHH82d/9meFNPF3f/d36devX7785S93XHfjjTdmu+22y5lnnpmzzjord955ZwYMGJDLLrsszc3vZnLdsQ0AAACA6qgp3DrnnHNy+umn5+CDD87KlStz/vnn5+GHH861115bSBP/8i//ssFtw4YNy4033li3bbAx666L0dIyaovXxQAAAAA2X03hVktLS+6+++7cfffdaWtry4gRI3L77bdbp4peyboYAAAAUB41hVtJssMOO+S0007rzl4AAAAAYJPUFG4tW7YsN910U5599tmsWLGi07apU6d2S2MAAAAAsDE1hVtf+cpXsnr16hx++OEZMGBAd/cEAAAAADWpKdyaM2dO/uVf/iX9+/fv7n4AAAAAoGbNtdzoz//8z/PCCy90dy8AAAAAsElqGrl1ySWX5LTTTsu+++6bIUOGdNp2xhlndEtjAAAAALAxNYVbV111VV555ZXssssuWb58ecf1TU1N3dYYAAAAAGxMTeHWPffck/vvvz/Dhw/v7n4AAAAAoGY1rbm16667pm/fmnIwAAAAAKibmhKrY445JpMmTcqJJ574R2tu7b///t3SGAAAAABsTE3h1i233JIk+e53v9vp+qampjz00EPFdwUAAN2grW185s59PknS0jIqI0fukWnTpvdwVwDAlqgp3Hr44Ye7uw8AAOh2a4OsYcO2zauvLuvhbgCAItS05hYAAAAAlJFwCwAAAIDKEm4BAAAAUFnCLQAAAAAqq6YF5ddasmRJVqxY0em6XXfdtdCGAAAA4L2c7RTYkJrCrUcffTTnnXdeFi9enPb29o7rm5qa8uyzz3ZbcwAAAJA42ymwYTWFW5MnT86kSZNy7LHHZqutturungAAAACgJjWFW2+88UaOP/74NDU1dXc/AAAAAFCzmhaUb2try7Rp07q7FwAAAADYJDWN3Hr66adz88035wc/+EGGDh3aadstt9zSLY0BtbO4JgAAAL1VTeHWhAkTMmHChO7uBdhMFtcEAACgt6op3Dr22GO7uw8AAAAA2GQbDLfuvPPOfPrTn06S3H777Rss8Jd/+ZfFdwUAAAAANdhguHXPPfd0hFt33XXXem/T1NQk3AIAAACgx2ww3PrBD37Q8f+bb765Ls0AAAAAwKZo7ukGAAAAAGBzCbcAAAAAqCzhFgAAAACVJdwCAAAAoLK6DLdmzJjR6fILL7zQ6fKNN95YeEMAAAAAUKsuw63zzjuv0+Xjjz++0+Wrr766+I4AAACgAtraxqelZVSSpKVlVNraxvdwR9A79e1qY3t7+yZdBgAAgN5i2rTpSZJhw7bNq68u6+FuoPfqcuRWU1PTJl0GAAAAgHrqcuRW8u7orLX/1ncZAAAAAHpKl+HWihUr8t/+23/ruNze3t5xub293cgtAAAAAHpUl+HWQw89VK8+AAAAAGCTdRlufec738n3v//9evUCAAAAAJukywXlZ8+eXa8+AAAAAGCTdRluAQAAAECZdTktcdWqVTn77LO7LHDZZZcV2hAAAAAA1KrLcCtJ3v/+99ejDwAAAADYZF2GW/37988ZZ5xRr14AAABoIG1t4zN37vNJkpaWUUmSkSP3yLRp03uyLaDBdBlutbe316sPAAAAGszaEGvYsG3z6qvLergboFF1uaD80UcfXa8+AAAAAGCTbTTcuvzyy9e77YorrsicOXO6pSkAAAAANl1b2/iOacAtLaPS1ja+hzvqfl1OS7zuuuvy13/91+vd9pGPfCRTpkzJlClTuqUxAAAAADZNb5wO3OXIrWeffTYHHnjgercdcMAB+e1vf9stTQEAAABALboMt5YvX5633357vdveeeedvPnmm93SFAAAAADUostwa/fdd88vf/nL9W775S9/md13371bmgIAAACAWnQZbn3uc5/Lt771rcycOTNr1qxJkqxZsyYzZ87Mt7/97Zx88sl1aRIAAAAA1qfLBeXHjx+fxYsX52//9m/z9ttvZ/DgwVm6dGn69euXL3/5yxk3bly9+gQAAKBO2trGZ+7c55O8e7a1kSP36FikGqBsugy3kuTkk0/OhAkT8tRTT2Xp0qUZPHhwRo8enUGDBtWjPwAAAOqsN55tDaiujYZbSTJo0KANnjURAAAAAHpKl2tuAQAAAECZ1TRyCwAAgHJbd52sxFpZQO8h3AIAAGgA64ZY1soCehPTEgEAAACoLOEWAAAAAJUl3AIAAACgsoRbAAAAAFSWcAsAAACAyhJuAQAAAFBZpQq3nnzyyey1117553/+547rFi9enL/5m7/JEUcckaOPPjpPP/10t24DAAAAoDpKE24tX748V1xxRT7xiU90uv7KK69Ma2tr7r///px//vk566yz0t7e3m3bAAAAAKiO0oRbl1xySU455ZRst912na6/7777cvzxxydJWltb079//zzzzDPdtg0AAACA6ujb0w0kySOPPJJly5Zl7Nix+cUvftFx/euvv5729vZsv/32HdeNGDEir7zySnbdddfCt+2zzz6b1PeQIYM249H+sWHDti2kTpG19FTfOkXWKludImvpqb51iqxVtjpF1tJTfesUWatsdYqspaf61imyVtnqFFlLT/WtU2StstUpspae6lunyFplq1NkrUbvqTvUJdw69thjM3/+/PVuu++++3LllVfmhhtuqEcrhVqyZHnWrNmy6YzDhm2bV19dVkg/RdXSU33rFFmrbHWKrKWn+tYpslbZ6hRZS0/1rVNkrbLVKbKWnupbp8haZatTZC091bdOkbXKVqfoWo3cU5G1GrmnRn5sZfz93Zjm5qbNGkhUl3Drjjvu2OC22bNn59VXX82ECROSvDtaa9asWVm6dGnOOOOMJMlrr73WMdJqwYIF2XHHHTumLxa5DQAAgMbW1jY+c+c+nyRpaRmVJBk5co9Mmza9J9sCtkCPr7nV2tqaJ554Ig8//HAefvjhHHHEEfnSl77UEWyNHTs2t956a5J3g7CVK1dm77337rZtAAAANK5p06ZnzpznMm/evMyZ81zmzHlOsAUVV4o1t7py5pln5qyzzsqdd96ZAQMG5LLLLktzc3O3bQMAAACgOkoXbl1yySWdLg8bNiw33njjem/bHdsAAAAAqA7DlQAAAACoLOEWAAAAAJUl3AIAAACgsoRbAAAAAFSWcAsAAACAyhJuAQAAAFBZwi0AAAAAKku4BQAAAEBlCbcAAAAAqCzhFgAAAACVJdwCAAAAoLKEWwAAAABUlnALAAAAgMoSbgEAAABQWcItAAAAACpLuAUAAABAZQm3AAAAAKgs4RYAAAAAldW3pxsAAACA3qytbXzmzn0+SdLSMipJMnLkHpk2bXpPtgWVIdwCAACAHrQ2xBo2bNu8+uqyHu4Gqse0RAAAAAAqS7gFAAAAQGUJtwAAAIDSa2sb37EmWUvLqLS1je/hjigLa24BAAAApWdtMjbEyC0AAAAAKku4BQAAAEBlCbcAAACAXuO9a3dtyfpd1gErB2tuAQAAQANoaxufuXOf77jc0jIqI0fu0bFWFe8qcu0u64CVg3ALAAAAGsC6IZawhd7EtEQAAAAAKku4BQAAAEBlCbcAAACATiyUTpVYcwsAAADoxELp9bXuyQDWhopOBlA74RYAAABADxImbhnTEgEAAACoLOEWAAAAAJUl3AIAAACgsoRbAAAAAFSWcAsAAACAyhJuAQAAAFBZwi0AAAAAKku4BQAAAEBlCbcAAAAAqCzhFgAAAACVJdwCAAAAoLKEWwAAAABUlnALAAAAgMoSbgEAAABQWcItAAAAACpLuAUAAABAZQm3AAAAAKgs4RYAAAAAlSXcAgAAAKCyhFsAAAAAVJZwCwAAAIDKEm4BAAAAUFnCLQAAAAAqS7gFAAAAQGUJtwAAAACoLOEWAAAAAJUl3AIAAACgsoRbAAAAAFSWcAsAAACAyhJuAQAAAFBZwi0AAAAAKqs04dbNN9+csWPHZvz48TnmmGM6rn/rrbfy1a9+NYcffnjGjh2bWbNmdes2AAAAAKqjb083kCQzZ87Mfffdl9tvvz2DBg3K4sWLO7Zdf/31GTRoUB544IG89NJLOeGEEzJz5sxss8023bINAAAAgOooxcitqVOn5owzzsigQYOSJEOHDu3YNmPGjBx33HFJkt122y177713Hn300W7bBgAAAEB1lGLk1ty5c/P000/nf/yP/5FVq1bl+OOPz1/91V8lSebPn5+dd96547YjRozIK6+80m3bNsWQIYM2+T7rM2zYtoXUKbKWnupbp8haZatTZC091bdOkbXKVqfIWnqqb50ia5WtTpG19FTfOkXWKludImvpqb51iqxVtjpF1tJTfesUWatsdYqs1eg9dYe6hFvHHnts5s+fv95tjz/+eFavXp0FCxbkf/7P/5nXX389n/nMZ/Knf/qnGTNmTD3a22xLlizPmjXtW1Rj2LBt8+qrywrpp6haeqpvnSJrla1OkbX0VN86RdYqW50ia+mpvnWKrFW2OkXW0lN96xRZq2x1iqylp/rWKbJW2eoUWUtP9a2zVpl6avTnu4w9bUxzc9NmDSSqS7h1xx13dLl9p512yrhx49Lc3JwhQ4bkgAMOyG9+85uMGTMmO+20U+bNm5ftt98+SbJgwYLst99+HfcrehsAAAAA1VGKNbfGjRuXxx57LEmyYsWK/Nu//VtGjRqVJBk7dmxuu+22JMlLL72UZ555JgceeGC3bQMAAACgOkoRbn3uc5/LggULctRRR2XChAkZP358PvaxjyVJTjnllLzxxhs5/PDDc/rpp2fy5MkdC893xzYAAAAAqqMUC8pvtdVWufzyy9e7beDAgbn66qvrtg0AAACA6ijFyC0AAAAA2BzCLQAAAAAqS7gFAAAAQGUJtwAAAACoLOEWAAAAAJUl3AIAAACgsoRbAAAAAFSWcAsAAACAyhJuAQAAAFBZwi0AAAAAKku4BQAAAEBlCbcAAAAAqCzhFgAAAACVJdwCAAAAoLKEWwAAAABUlnALAAAAgMoSbgEAAABQWcItAAAAACpLuAUAAABAZQm3AAAAAKgs4RYAAAAAlSXcAgAAAKCyhFsAAAAAVJZwCwAAAIDKEm4BAAAAUFnCLQAAAAAqS7gFAAAAQGUJtwAAAACoLOEWAAAAAJUl3AIAAACgsoRbAAAAAFSWcAsAAACAyhJuAQAAAFBZwi0AAAAAKku4BQAAAEBlCbcAAAAAqCzhFgAAAACVJdwCAAAAoLKEWwAAAABUlnALAAAAgMoSbgEAAABQWcItAAAAACpLuAUAAABAZQm3AAAAAKgs4RYAAAAAlSXcAgAAAKCyhFsAAAAAVJZwCwAAAIDKEm4BAAAAUFnCLQAAAAAqS7gFAAAAQGUJtwAAAACoLOEWAAAAAJUl3AIAAACgsoRbAAAAAFSWcAsAAACAyhJuAQAAAFBZwi0AAAAAKku4BQAAAEBlCbcAAAAAqCzhFgAAAACV1benGwAAAAAaU1vb+Myd+3zH5ZaWURk5co9Mmza9B7ui0Qi3AAAAgG6xbog1bNi2efXVZT3YDY3KtEQAAAAAKku4BQAAAEBllSLcevHFF3PSSSflmGOOyZFHHpnvfe97HdveeuutfPWrX83hhx+esWPHZtasWd26DQAAAIDqKMWaW5dffnmOOOKInHjiiXnzzTczbty4HHTQQdlnn31y/fXXZ9CgQXnggQfy0ksv5YQTTsjMmTOzzTbbdMs2AAAAAKqjFCO3mpqasmzZu4vKrVy5Mk1NTdl+++2TJDNmzMhxxx2XJNltt92y995759FHH+22bQAAAABUR1N7e3t7Tzcxb968TJw4MUuXLs0bb7yRs88+OyeccEKSZPTo0XnooYc6wq5vf/vb+ZM/+ZOcfPLJ3bINAAAAgOqoy7TEY489NvPnz1/vtscffzy33XZbjjnmmJx66qlZtGhRTjrppOy9997Zd99969HeZluyZHnWrNmybLDIU6EWVUtP9a1TZK2y1Smylp7qW6fIWmWrU2QtPdW3TpG1ylanyFp6qm+dImuVrU6RtfRU3zpF1ipbnSJr6am+dYqsVbY6RdZq9J42prm5KUOGDNrk+9Ul3Lrjjju63H7zzTfnwQcfTJIMHz48H/3oR/OrX/0q++67b3baaafMmzevY5TVggULst9++yVJt2wDAAAAoDpKsebWLrvsksceeyxJsnz58vzbv/1b9thjjyTJ2LFjc9tttyVJXnrppTzzzDM58MADu20bAAAAANVRirMlXnzxxbnwwgszderUvPPOO/nUpz6Vgw46KElyyimn5Jxzzsnhhx+e5ubmTJ48OYMGDeq2bQAAAABURynCrb333ju33nrrercNHDgwV199dd22AQAAAFAdpZiWCAAAAACbQ7gFAAAAQGUJtwAAAACoLOEWAAAAAJUl3AIAAACgsoRbAAAAAFRW355uoMqam5v+f/bOOyqq6/vbH3qVYkdpYo9GRVBUQEFpUhREQWM3JhgjarC3xBZjidFEjZqYxBIriCgiAtKLigrSRYrSOyKdGZjz/sFv7iuWeAeuiHzPs1bWClx43HtzZs/MmXPP6VAeLl00pvb1cOnqaB4uXTSm9vVw6epoHi5dNKb29XDp6mgeLl00pvb1cOnqaB4uXTSm9vVw6epoHi5dNKb29XDp6mgeLl2dPaYP8e+IEUIIx7FQKBQKhUKhUCgUCoVCoVAo7QK9LZFCoVAoFAqFQqFQKBQKhfLJQie3KBQKhUKhUCgUCoVCoVAonyx0cotCoVAoFAqFQqFQKBQKhfLJQie3KBQKhUKhUCgUCoVCoVAonyx0cotCoVAoFAqFQqFQKBQKhfLJQie3KBQKhUKhUCgUCoVCoVAonyx0cotCoVAoFAqFQqFQKBQKhfLJQie3KBQKhUKhUCgUCoVCoVAonyx0cotCoVAoFAqFQqFQKBQKhfLJQie3RIQQAkJIh/EAgEAg6FAeCoVCoVAoFAqFQqFQKJT2gk5uiYiYmBjExMQAtG2CiisPAIiLc/Nn5MojhKvJu44KV/lxXae2TFK+GotAIGhTbFy6XvVwRUeczKUT1e+nrblxNS4/xPgWujqSp60u2lM+Hp05t45KR3z8dmZovdsXWm8KhdLRkdi+ffv2jx3Ep0BGRgaCgoJw+vRpVFZWom/fvpCVlWUmqNrbAwCJiYm4fPky/vzzT5SXl0NKSgrdu3cX2cWV53Xa+vtvgxDCiZcLD1f5ceHh8XiIiYmBqqoqpKWlme8LBAKR/GJiYkhLS4OCggKkpKRaTMCKGidXLq5y49JVXl6OyMhIyMjIQFxcnMnvY8bEZZ24yo8rD5e5cTUuuXysdMQxQHtK+7o64mOlo+XGpYv28E/TA9B6t7eL1lt02vr7wP9/XhNOBLbWx5VHCBe5ce3qzPUGOmedPiRipLMvr+GA+vp6zJ49G4aGhpCWlkZAQAAKCwthYGCA1atXY+DAgaxeXHPlAYC6ujrY29tj/vz54PP5iIyMRElJCdTU1ODi4gJdXV1WuXHleZXGxkbExcWhqKgIurq6UFRURJcuXQA0P7BEXSH27Nkz5Ofnw8DAAJKSksz3RX1Dw5WHq/y48nh5eSEyMhKFhYWIjY3FsGHDMHPmTMyaNYt1TgAQEBCAkJAQlJeXIyUlBVpaWpg7dy4sLCxE8nDp4io3Ll0XLlxAdHQ0ioqK8Pz5c3z22WcwMjKCk5MTFBQUPkpMXNaJq/y48nCZG1fjksvHSkccA7SntK+rIz5WOlpuXLpoD/80PQCtd3u7aL1Fh8fjtZi8A1r/gfrrLuHkRGsmhD+EB+Aut9a6OnO93+YCOk+dPhiE8l7Onz9PXF1dW3wvNzeXbNu2jbi6upKqqqp29RBCyJUrV8jy5ctbfK+oqIjs37+fzJ49m+Tn57er51VWrFhB1q9fT+zt7YmpqSlZsWIF8fT0FNlDCCEbN24ka9asIdOmTSOff/45WbJkCQkODv5oHkK4y48rz4wZM4ivry/h8XikpqaGnD59mlhaWpJp06aRlJQU1h4HBwdy5coVkp6eTrKysshvv/1G7OzsiKurKykoKBApJq5cXOXGpWvGjBkkKiqKEEIIj8cjXl5eZO7cuWTixIkkIiLio8XEZZ24yI9LD1e5cTUuuXysdNQxQHtK+7k64mOlo+XGpYv28E/TI3TRerdvTLTe7Hj69Ck5fvw4sbW1JY6OjuTkyZMkOTlZZA8hhDx//pxcvHiRLF26lDg5OZF///2XvHz58qN5uMyNK1dnrjchnbtOHxo6ucWCK1eukL1797712saNG8mpU6fa1UMIIT4+PmTLli1vvbZ//37yyy+/sPZs3ry5zR4h8fHxxMHBgQgEAkIIIWVlZeTs2bPE0tKSzJ49m5SUlLB2xcXFEQcHB1JYWEgIaZ50O3ToEDE0NCRubm6ktra2XT1c5seV5/nz58TW1vat144fP04OHz5M+Hz+ez0ZGRnExsbmje+/ePGCbNu2jfz1119MrO3l4io3Ll25ublk2rRpb52IvnbtGtm1axepr69v15i4rBNX+XHl4TI3rsYll4+VjjgGaE/5NHtKZ86NSxft4e1bJ1rv9q9TR+spnb3eQlxdXcnevXvJs2fPyLVr18jKlSuZD65zcnJEcrm5uZFNmzaRqKgocubMGeLg4EBGjBhBNm/eLNL7KK48XObGlasz15vL/DpinT40dEN5FkyePBlRUVFYtGgR/Pz8UFtby1yrqamBiooKa094eDi+/PJL+Pv7o6amplUeALC2tkZJSQlsbW1x5coVVFVVMddycnKgrq7OymNpaYmKigpYWVm1ySMkMTER/fr1Y5Ymdu3aFfPnz8ft27cxcuRIBAYGsnY9fPgQI0aMQK9evQAAPXv2xOrVq3H79m1IS0sjNDS0XT1c5seVR0NDA8OHD8cPP/yAkgXX99sAACAASURBVJKSFtdMTEwQHBzc4hbMd9GrVy+oq6vjl19+QXl5OfN9FRUVzJgxA/7+/qyXm/bs2ZMTl7q6Oie5AdzVqW/fvpg8eTJ27NiBgoKCFtdGjx6NiIgIyMjItGtMXHkA7vLjysNlblyNca7GN8DdGOeyTrSnfJo9pSOOAS77ZUfrTQDt4bTeHbNOHa2ndPZ6A823aaWkpOCbb76BtrY27O3t8euvv8LDwwNKSkrw9vZm7WpoaMCjR4+we/dujB8/HgsWLICnpydu3ryJ+vp6hISEAHj/YVRcebjMjStXZ643l/l1xDq1B3RDeRbIysrCzs4OYmJiCAsLw7Vr1xAYGIiEhATExcVhy5Yt723MjY2NUFRUhKOjI0pLS3H37l14eXkhJCQEcXFxiI+PZ+UBgOjoaIiJieGLL76AuLg4wsPDceLECdy6dQvx8fF4/vw5Nm7c+F5XQ0MDMjIy4OzsjJ49e8LPzw8nT54U2fMq2tra8PHxQVpaGoYPH97iyUF4b/vEiRNZuXr37o0zZ86guroagwYNYu7vlZaWxsOHD1FSUgJDQ8N28wCAlpYWbt261eb8uKqTmJgY+vXrh+DgYHh7eyMpKQk1NTVQUFDA+fPn0bVrV0yePPm9HmlpaWhpaSEoKAgPHjxAdnY26uvroaqqCg8PD0hJScHMzOy9HqGrX79+CAkJQXR0dKtd4uLi0NHRQVhYGLy9vZGYmNiq3IDmOmlrayMkJKRNdQKaXxRFRkbijz/+QGRkJCorK0EIwalTp6CjowMTExPWMQnr1JaYxMTEoKOjg9DQUKZO1dXVrcoNaH4hGhUVhZMnTyIqKqrV+fXt2xfh4eH4888/W+3hanwD3I1xrsY3wN0Y53J8057yafYUrvqJ0MVVT+GqnwDc9BShh/bw90PrzY6OVm+hq6P0lP+FevP5fOTn56OmpgZDhgxhvi8nJ4eRI0di//79sLa2hpyc3HtddXV1yMzMhLy8PDQ1NZnvKysro2/fvjhy5AimTp0KWVnZdvFwmRtXrs5cby7z64h1ag/ohvLv4eLFi4iNjUVBQQGsrKygp6eH/Px8pKWlQVJSEjY2Nujdu/d7PcuWLYOBgQEmTpwIFRUV1NfXw8/PDy9evECXLl0wffp0ZmXR+1i0aBFcXFwwfvx4AEBoaCjk5eWRk5MDBQUFjBs3DsrKyu/1bN26FcnJyUhNTcWNGzdQVlYGMTExZGdnQ1FRkbVHCPm/jemio6Nx7NgxlJeXo1+/fjA1NYWSkhJ+/vlnHDhwAMOHD2ftCgoKwqVLl5gnRz09Pairq2PVqlU4cOAARowYwSq20NBQXLx4EYSQNnkA4NGjRzhy5AjKysqgo6ODSZMmQVlZWaT8AOD+/fs4evQoKioq2uQREhISgsePHyMuLg6ZmZlwdHTEjBkzRFp9l5OTg5CQEGRnZ6OoqAjR0dGwtrbGokWLWjQzNiQnJ+Phw4fIyckR2VVdXQ1ZWVlISkri5cuXePToEeLi4pCQkICMjAyRc2tqaoKEhASampoQGhqKuLg4JCYmIj09vVV1AoCnT5/i3r17uH37Nng8HqZPnw4LCwvWj+NXCQ4ORmJiIh4/ftzqmCorK/Hw4UMkJiYiMTERqampInlevnwJeXl5SElJMflFREQgODgYdXV1IuXH5/M58bwKF+Mb4G6Mt2V8A9yO8Q8xvgHaU/6LjtxTuOgnQNt6Cpf9BPgwPYX28HdD6/3p11vo6ig9pbPXOygoCNu3b0efPn3g4OAAW1tbKCgowMvLC9euXcOZM2dYu9zd3fH7779jzJgxMDc3h6GhIeTl5REYGIjTp0/j3Llz7eoJDg7G9u3boaamhhkzZsDGxqbVuQUGBmLHjh3o06dPm1ydud4AdzXnqt7C/I4dO4axY8fCzMwMRkZGrc7vQ0Int/6DxMREbN++HUuWLEFDQwP8/PywceNGaGtrA2hu1EpKSu/1lJWVwdHREU1NTZCSksLQoUMxffp0HD16FJcuXYK8vDzrmOLj4/HDDz/g2rVr4PF4OHz4MEJCQiAhIQE9PT2sXbsWioqK7/UkJSVh+/btcHd3h5+fH3x9fZGVlYXGxkbo6upi3bp1zMl9rSU2NhZ3795FUFAQ+vfvD3Nzc1afrpPXTm8oLy/H3bt3kZKSggcPHkBKSgozZ86Evb29SPHk5uYiLi4OT548wYMHDyApKSmSJycnBxoaGszXMTExiIqKQnh4OLS1tVnn9/qpEq31ZGRk4PHjx7h37x4mTpyIiRMnMpORwjdebCgpKUFSUhLy8vIwdepUdO3aFTk5OZCWlkaXLl0gJibGalYfaJ6wGz58eIuTZrKysiArKwslJSVISEi8cVrH2zh69CiGDRuGiRMnvpFHY2MjJCQkWN/SdPfuXdy4cQOVlZXYu3dvi3EtiisxMREhISGIiYnBpEmToK+vj2HDhgEQrd4AkJ2djfv37zMTBgMGDEBlZSUUFRVBmvdCZLVi0tfXF/369YO2tjbzaUlxcTGUlJQgJSUFcXFx1nXas2cPRowYAVtb2zeuiZLfnTt3cOHCBZSVleHEiRNQU1NrlYer8Q1wN8a5Gt8Ad2Ocq/EN0J7yqfYUrvoJwF1P4aqfANz1FNrD27eH03q3b72BjtdTOnu9X4fH48HDwwMRERF49OgRNDQ0oKmpCUtLS1haWorkevbsGXx8fJCeno6cnBwQQqCmpgZLS0tMmzaNtScjIwO3b9/G06dPkZeXB4FA0CpPfX09PDw8EBYWhvj4eKirq7c6Nx6PhytXrrRwaWhowMrKSiRXZ643wF3Nuao3ADx//hw3b95k8mttnT4kdHLrP9ixYwe0tbWxcOFCCAQCHDx4EOXl5fjpp5+QmZmJnTt34vTp06xcoaGhzKcdPj4+OHv2LPLy8mBra4upU6di0qRJrDyenp6IjIzEwYMHcenSJURERODo0aMoLCzEnj17YGdnB3Nz8/d69uzZAyUlJaxYsQL//vsvfHx8cPHiRRQUFODHH3/E1KlTYWNjwyomoPkFfUhICDw9PcHj8WBpaYnRo0ejf//+zHW2L66bmprw+PFj+Pn5QUlJCfPmzYOSkhLq6+shLy//1uNM34bwwWxsbAwNDQ2IizdvMZeXl4e+ffu2+OTmfdTX12PlypXYsWNHiydCIWxdPB4Pf//9N86dOwcDAwP8/PPPTFyieOrr6zF79mwYGhpCSkoKAQEBKC4uxvjx47F8+XIMGTIEAoGghfttNDQ04JtvvoGcnBxUVFTQpUsXbNiwoVXHuTY0NGDkyJGQlJSErq4u5syZA2tra5w+fRpTp05l/SlYXV0dpk2bBi8vLygoKCAuLg6nTp2CQCDA7NmzYWxszPr42vr6ejg4OMDFxQUxMTEwMDDA/fv3UVZWBmdnZ0ycOJGVq66uDvb29pg/fz74fD4iIiJQWloKNTU1LF26FPr6+qzqLYxp8eLFGDJkCCQkJFBZWYldu3aJtL8D0DyWRo8eDTU1NfTv3x/GxsaYOXMmjh49CltbWwwePJi1S5ifp6cnFBQUEBERgd9//x1KSkqYOnUqpk+fLpJnx44dCA4OhoaGBu7evYumpiZYWVmxnkjmanwD3I1xrsY3wN0Y52p8C120p3x6PYWrfgJw11O46ievutraU2gPb98eTuvdvvV+1dVRekpnr7eQxsZGPH78GAUFBdDX14ecnBzk5ORQXV2NlJQUjBo1itWiAyHp6ekoKyuDgYEBamtrkZeXBz6fj5ycHIwcOZLV3UJlZWWQl5eHrKwsxMTEUF1djcLCQvB4PGRnZ0NXV5fV8+etW7cgKSmJyZMnt3gPV15ejuTkZJFyKykpga+vLyQkJDB37twWrpSUFIwcOZKVqzPXG+Cu5lzVW0hGRgby8/MxYcIEiImJoaSkBKWlpcjKyoKenl6rVpZ+KOieW//BX3/9BWtra6irqzO3xZ09exbGxsYIDw+HtLQ0jIyMWLk0NTVx7tw5lJaWYtGiRUhJScGYMWMgLi6OmpoajBkzhpWnT58+CA0NhZqaGkpKSjB69Gjo6OhAUVERGRkZyM7OZhVTVVUVHj16hC5duuC3337DwoULMXToUHTp0gVpaWnIy8tjnRsAeHh44PLly/jiiy8gLy+P4OBgeHh4ID4+HkOGDIGqqipr182bN/H3339DR0cHeXl5yM7OxtixYyElJQWBQMB6kiw0NBQbNmxATEwMwsPDISUlBTExMfz111+YNGmSSHuJXblyBcXFxZg1axaKi4vh4eGBlStXIikpCd26dWO9NNvT0xP379/Hnj17kJiYiIqKCqxcuRLx8fHo1q1bi5Vh74unqqoKu3fvxrhx4zB37lzY2NggKSkJ4eHhMDY2ZvVC5OrVq6isrMShQ4fQu3dvXLlyBbW1tRg1ahQA4MSJE/j8889Z1aqurg6EEOjp6eGzzz7Dr7/+isOHDyM0NBTm5ubo06cPq9wCAgJQUlKCGTNmIDY2Fnv37oWNjQ0EAgH+/PNPjBs3Dj169GDlunr1Kvh8PlauXAk+n4/du3fDwcEBAoEAx48fx5gxY1g1ZC8vL1RWVmLTpk3Q1dXF9OnTMWXKFGRlZcHT0xOGhoasVnECzWOgrq4Ou3fvxsCBAxEQEIDk5GQYGxsDAHbt2sWM9/+isbERMjIykJOTg6GhIW7cuIGTJ08iNDQU48ePR/fu3Vnf+x4SEoL8/HzMmDEDMTExOHjwIJYvXw45OTmcPHkSQ4cOZTXGhStKv/zyS0hJSWHHjh347rvvICsrixMnTmDAgAHQ0tJ6r4er8Q1wN8a5Gt8Ad2Ocq/EN0J7yqfYUrvoJwF1P4aqfANz1FNrD27eH03q3b72BjtdTOnu9haxatQppaWnMirCkpCQ0NjZi9OjR0NTUZN57sGHXrl0IDQ1FWFgY0tLSYGJigm7duqFHjx4YMGAA68kIe3t7PHjwALW1tVBQUEDPnj2Rnp6Obt26QU9Pj7Xn+++/x+TJk6GhoYGqqiq4u7sjLS0N2traGDJkCOuV6gCwfPlyNDU14fr169DQ0EBKSgoSEhKgoaEhkqsz1xvgruZc1RsANm3ahPv378Pb2xv79+9HfHw8+vbtC319fQwcOBAKCgqt+gDzQ0FPS/wPNmzY0GLGVk1NDWZmZjh16hS8vb1FWn4nLi6O/fv3Izs7Gzdv3sS9e/fg5uaG77//HsuXL2ftUVZWhr6+Pr766iucOXMGHh4eqK6uRkVFBYKCgmBnZ8fKM2HCBPB4PPz888+YN28esrOzUVdXBwCIiIgQeWnhzZs3sXjxYkyZMgVff/01/vnnHxw5cgR8Ph9//vmnSK6rV6/C1dUVrq6ucHJyQkBAAHOi4d27d/HHH3+w8gwbNgwODg6YOXMm9PT0cOLECcyZMwehoaF48uQJqqurWccUGxvLbC555MgRFBQU4JdffkGPHj1w4MABvHjxgpXHx8cHzs7OGDJkCKqrq3Hv3j0cOHAAPXr0wN69e984SeZdSElJoW/fvi2+17dvX+zcuRMKCgq4fPkyK4+/vz+zkeewYcPg6uoKPz8/CAQChIaGIiEhgfUkQpcuXbBw4ULk5ubCyMgIERERcHJygra2NubOnYtly5ax8qipqTGToU+ePIG5uTkcHR2xfv16LFy4UKTTPUpKSjB06FAAzW9wZ86c2cLl4+PDyqOoqPjGBG3Pnj2xfv16jB49GpcuXWIdk7+/P3NYgJqaGlatWoW4uDi8fPkSYWFhyMnJYXXLloyMDPMCTV1dHRcuXICZmRkGDRqEffv24ccff2Qdk6amJmRkZFBXV4e8vDxYWlpi4sSJWLJkCXOyKBvq6uqgo6MDoHmyRLiS5csvv8TKlSsREBDAysPV+AYAPz8/TJkyBUDbxjhX4xtoPuSCizFeUlKCzz77DEDbxjfAXc1v377NSb2B5povWrSozTXv1asXpz2Fi5orKChw0lP8/PyYld9t6SdAc09ZunRpm3uKhoYGJ/0EaD5JmoueIlxJ+Cqt7eG3b9/ucD1cXV2dk5pXV1dzUm8FBQXO6t2ZnzNra2s5qTfA3euUgIAATnqKsN6SkpJtrreWlhZT79zcXE5eo1y+fLlN9QaAhIQE5OXlYe/evbh27Ro8PDygr6+PkydPYvbs2SgpKWH9pj8xMRFJSUlwdXXFmjVrEB8fj/PnzzPXg4ODwePx3uupra3F8OHD8ezZM3h7e+PLL7/EmjVr8O2336KoqIh1bikpKairq8OYMWNQV1eHdevWITY2Fp6enrC1tUV8fDxrV1JSEhoaGrBr1y78+eef2L17N4KCguDh4QFbW1vExsay8nTmegPc1ZyregPN2yGlpqZi3bp1uHHjBvz9/TF48GBs2rQJa9asQU1NTYea2ALo5NZ/Mnz4cGaTWoFAAABwcnJCeHg46urqmBe4bGhqaoK0tDSmTp2K06dPY8SIEZCWlmb1wHmdOXPm4NatW3ByckJOTg5MTEywb98+TJkyhXVMKioqOHr0KDw9PTFt2jQ8e/YMFhYWcHJywoABA0TObcSIEW88iHV0dPDLL78gPT0dDx8+ZOUqKipCSUkJ9PX1ATQfyWtvb48rV64AaP5EqXv37qxcvXr1wtKlS3H//n1mOXO3bt3w2WefYcGCBYiOjmad48SJE/H48WMAzfnOnz8f+vr62LBhA1RVVZGYmPheB4/HQ8+ePSEnJ4fKykrExMRg9erVGD16NDZu3IiuXbsiOTmZVTyTJ09GVFQUFi1aBD8/P9TW1jLXampq3nhR+a54hLeONjU1gcfjwdDQEN26dUNQUBACAgJEOi1GIBCgR48ecHR0ZJ4gUlNT8dtvv+HJkyfYtm0bK4+uri54PB6cnZ1x9+7dFrkkJCQwL0zYYGJiglOnTsHY2BhFRUXMRBfQ/CZ30KBBrDxTpkxBeXk5rKysmBUuQnJyclivQuDz+TA1NYW6ujqamprA5/MxZMgQDBo0CP7+/vDz82N1W7EQ4b5xvr6+4PF4ePLkCfbt24egoCCsXbuWtWfw4MHo378/7O3t4efnBz6fz1wLCwtj3Q8mT54Md3d3GBoagsfjtViJePfuXdYHN0yePBnh4eH48ssv4e/vj5qaGuYa2/ENNI9xPT09po/z+XwYGhpCVVVV5DEuHN+zZs3ChQsXADSPoV9//VWk8Q0097X6+nrMmTMH9+7da/UYNzExwYkTJ2BiYtJiIlcYG9vxDQDm5uZMzQMCAlpVcx6Ph3HjxjH1bmxsbFNPAYDu3bvDyckJFy9eBNC6nqKnp4f6+np88cUXuH//fpt6ipmZGSc1t7a2RklJCWxtbVvdU5qammBjY4OePXsCQJv7CQBISEjA2dm5TT1lyJAh0NLSgqOjY5v6CQDY2dnh0qVLMDY2blNPsbW1RVlZGWxsbODu7t7qHi4QCDBz5kxm1WBjYyOGDBmCwYMHt7qHOzk5wdfXF3w+v9U9fOjQoejXrx9mzJgBf3//VtfcyckJly9fhpGREfh8fqvrbWlpiYqKijY/ZzY2NsLc3Bzq6upobGzk5DnT0dGRk+fMAQMGtPk508LCAh4eHswHzq2tNwCYmpqirKwMlpaWuHDhQqtqzufzMWnSJPTp0wcCgQBNTU1trreTkxOzoX1r6z1o0CDo6OjA3t4et2/fbnW9TU1N4e7uDiMjIzQ1NbWp3kDzBEm/fv2YN/ddu3bFggULcPv2bYwaNQpBQUGsXV5eXpg8eTL69++PkSNH4quvvkJgYCCA5r/f0aNHWa22kZeXx8aNG2FnZ4fjx4/j6tWrzN9y69at2LdvH6t4Xr58yWzDEh4eDjk5ORw8eBDnz5+Hq6srwsLCWOcWGRkJPT09AM37aOro6ODnn3/GhQsX4OrqipCQEFaezlxvgLuac1VvAHj48CFGjBjBrEjv1asXvvvuO9y+fRvS0tIIDw9n7Wov6J5bIiC8V/2ff/6BhIQEFixY0CpPfHw8ZGRkMHjw4DZvXgg0f9JWU1PTpvtdeTwe0tLSUFVVhc8//7zF5r1siI+Ph5ubG/r27Yu5c+fCwsICAFBaWop58+bBy8uL1fLjwsJC+Pv7w8rKinnBXllZiXXr1mHevHnMXmNsXMJ9voQvZE1NTeHq6oqbN28CAOv9HoDm+6nd3NxQXV3NNFNjY2OUlpZi8eLFcHd3ZxXT9evXsWHDBhgaGkJaWhqbN2+GhoYGeDwenJycWOcmEAhQU1MDX19f3L9/HxUVFVBQUIC6ujrCw8NZx5OXlwdpaekWt+RER0fj4MGDqKurg4eHB+ulqy9fvoScnBykpaXx22+/ITk5Gc+fPxfpU3qgeZ8doHlFwp07dxAYGIgpU6Zg+PDhCAgIwLlz51gvZefz+aiurmYmXrds2QIDAwP07t0bly5dgqenJytXUVERVFVVERAQAG9vbzx79gzKysoYPHgwUlNTcfbsWdYxZWVlQVlZucUb7KSkJGzYsIFZQsym5s+fP0fv3r0hKyuLM2fO4Pr168wKTlHJyclBnz59EBwcjGvXriEwMBDDhw+HoaEhYmJicOrUKVarbcrLy9G1a1dkZ2dDUlISq1evRo8ePTBo0CDcuXOH1bgUPm4bGhpw5swZpKSkMId39O7dGxEREazHd1NTE+rr69HY2AhlZWVmL6RHjx5h3759zGad76u3sE8Lny4PHz6M1NRU5OTkiLQ6Cvj/++oRQnDu3DlER0cjODgY5ubmGDp0KO7cucNqjAv7V3V1NZKSkqCoqIgffvgBo0ePhrq6ukjju7S0FN27d0dDQwNOnz6NJ0+eoLKyEjIyMtDU1ERkZCSrmpeVlYEQAikpqRb1joqKwqFDh9DQ0MC6p5SVlUFBQQEyMjIQCAT47bff8PTpU+Z2BLaUlJSgR48eIITg7NmzePjwIYKDg2FsbIyRI0ciMDCQdU8Rju/q6mokJCRARUUF27Ztw+jRo9GnTx9cuXKFVc2jo6Ohrq6OPn36MHtnpqWloWvXrhg4cCCePHnCqqc8evQIqqqq6NOnT4ufTU1Nxdq1a9HY2Mi6nzx48ABdu3Zl9sk8f/48rl69KnJPiY6ORq9evaClpQUvLy8EBQXB398fo0aNgoGBgUj95OHDh9DU1ETPnj2RlJSE7t27w9XVFT179sSAAQMQGBjIalx6eXlBRUUFJiYmuHjxIgIDA5GTk4Nu3bph4MCBSElJYd3Dvb29ISkpiUmTJkFeXp55PD958gTr168Hn89nVXPhz1hYWEBCQgJ//fUXfHx8UF1dDX9///fG8Xp+CgoKMDc3h6enJ/z8/BAaGopRo0Zh/PjxePjwIauaX79+Hd26dYORkRESExOhpKSEtWvXQk1NDQMHDoSfnx+rejc0NODZs2fQ1tZGUFAQvL29kZmZKfL4Bpr7ZXJyMjQ1NVusShJ1jPN4PCQnJzO30Jw9exZeXl6tes6sr69HWloaBg8ejIiICHh6euLOnTsij3Eej4ecnBxoa2sjPz8fkpKSWLVqlcjjW0hVVRVkZGRw//59+Pj4IDY2FioqKhg8eLBINS8pKYG4uDi6devGPPclJiZi06ZNIvWUkpISyMnJQVFRsU31Bpp7r3CvLT8/P9y4cQOff/45JkyYIFJPqa+vh6SkJDIzMyEnJ4c1a9agZ8+eGDRoEAICAkSqN9Bc83Xr1mHw4MFYunRpi8NFfvnlF9TW1mLr1q2sXJs3b4aJiQksLCyYvYW/+eYbzJ49G8XFxXj69Cm2bNnCOrZ//vkHT58+xU8//YSffvoJampqGDduHFJTU1nvUbZ7925IS0ujZ8+eUFBQwKxZswAAf/zxB/Lz88F2Z6MnT55gzZo1+Pzzz5Gamgo7OzssWbIEAHD8+HGUlJTg+++/f6+Hy3pv2bIFkyZN6lD1BpprLiMjgx49erS65lzVGwAKCgrg6uoKa2trODs7t5gf2Lt3LyQkJLBu3TrW+bUHdHKrlbDdfPZ/ierqapw9exbR0dF4/vw5tLW1oaqqCmVlZdYNEGh+Iwk0f4IsbDju7u7YvXs3Zs2axbpxCamoqMBvv/2GW7duwdHREevWrWPepIryN+TxeDh//jx8fX0RHx8PExMT9O7dG5KSkiLFJBAIUFxcjMePH+P48ePQ0tKCgoICmpqasH///vf+/sWLFxEbG4uCggJYWVlBT08P+fn5SEtLg6SkJGxsbFhtgHjp0iUkJSXh+fPnmDlzJtN8eTweXFxcICUlxfoW0IsXLyIhIQE5OTlYsGABDA0NceDAAejo6DCbm7LZ8+XixYt4/Pgx8vPzYW1tjbFjxyIrKwsZGRmQlZWFpaUlM+n5Pi5cuID4+Hjk5eUxG1E/fPgQN27cQENDA+zs7FjtK3fo0CE8efIESUlJuHDhAurr6yElJYXs7Gw0NDTAwMCAOVGOjSstLQ3x8fE4d+4clJWVoaSkBElJSWzZsgWFhYX466+/WHmePn2KhIQEXL58GTIyMvD19cWgQYNgYGAg0gEOhw4dQmpqKhITE3Hx4kXweDyIi4sjKysLTU1NMDAwYLVfwKFDh5CSkoLk5GRcunQJPXr0QHFxMcLCwpCVlYXp06czpzb9F8uWLYOBgQEmTpwIFRUV1NfXw8/PDy9evECXLl0wffp01hP5y5Ytg7GxMcaNGwcNDQ1IS0sjIyMDysrKcHNzY/brYOOZMGECDA0NmTf/X375JcaMGYNly5aJVO9ly5Zh3LhxMDY2RteuXcHj8eDj44OXL19CVVUVNjY2rPZ/cnFxwfjx42FsbAwdHR2IiYkhJiYGgYGBKCgogKOjIwwNDVnFtGHDBqxYsQIaGhoghCAyMhKEEJSVlaG8vBw2Njasar5x40Z89913zM8KJ4MAMLensKm30LVq1SrmU8ycnBycO3eOOWKbbc03btyIFStWMKsW7t27Bz6fjxcvXqCyshKWlpas99tav349Vq1axdy+2djYiKSkJERE7k8SDwAAIABJREFURCAnJwd2dnasar5o0SLm7wc07w8pLy+PnJwcKCgoYNy4cax6ysKFC/Htt99i7NixAJo/1VZVVUXfvn1F6ifCmJYvX864EhISEBMTA21tbUyaNIl1vV/PTfjpc3Z2NpSVlVn3E2F+y5YtY1yZmZkQFxdvUe/hw4e/12NhYQEFBQWsW7cOEyZMQENDA7Kzs/Hw4UPIy8vDxMSEdQ+3sLCAkpISvvvuuzf+1mvWrEFFRQWrmltaWkJRURFubm6M559//oGqqirs7e1F6imWlpZQUFDA2rVrmRVAWVlZePDgAVRUVDBx4kRWNbewsIC8vDzWr1+PCRMmAGg+Qczd3R3V1dVwdnZm1cO3bt2K5ORkpKam4saNGygrK4OYmBiys7OhqKjIenwDzW9Anz59iuTkZHh5eUFCQgIyMjJQU1PDtm3bWI/xrVu3IjU1FcnJycwqucjISGhpaYk0voWulJQUPHnyBDdv3kRZWRmA5g+cVFVVWY/xLVu2ICUlBampqbh16xZkZGTQ0NCAsLAw5Obmsh7fAPD7778jPT0dwcHBGDVqFGxsbPDZZ58hNzcXfD4fxsbGrPbbOnbsGJ49e4bAwEBoaWlh+vTpsLe3h6qqKtavX4+ysjJW9f7999+RmZmJwMBADBgwAPPmzUN1dTW0tLRgZGQkUr1///13ZGRkICgoCMOGDcP06dMxfPhwZGVlAQCMjIxY1fvYsWNIT09HSEgIBgwYAGdnZwwYMAAxMTHIycnBzJkzWY1vIcL3gdHR0Th27BjKy8vRr18/mJqaQklJCT///DMOHDjA+m9YXV2NqqqqFodWBQYG4vz58ygtLcWBAwdE2oQfAPbt24fq6moEBgbi5s2bzPMx29yePHmCAwcOIDc3FxUVFVizZg0GDRqEnTt3Yvfu3SKtwr1z5w4iIyNhZ2eHU6dOwcHBASNGjICLiwt+/PFH1rV/9OgRjhw5grKyMujo6MDExKTV9a6trW3xnoKLetfU1CAwMBDe3t6s6/0qaWlp2Lt3L3Jzc/Hy5Uu4ubm1quYhISEICwuDjY0N/v77b9jb24tcb+E4CAoKwqVLl5j9x/X09KCuro5Vq1bhwIEDIq94/OAQCqUNNDQ0EB6P1+J7ZWVlJCUlhfz7778kIyODNDQ0sHbx+fy3XsvNzSVTp04lAQEBrfKUlpaSffv2kdzcXEIIIY2Nja2OqaKigskvOzv7jfzf5eHxeEQgELT4flRUFPn++++Jp6cnKSsre68nISGBODo6Eh8fH+Lp6UlcXFzIs2fPmOsvX75klVdCQgKZMWMG41myZAl5+vQpc/3BgwekoKCAtevVmBYtWkQyMzNJXV0dEQgE5MWLF63yfP311yQjI4O5XlFRwcrzNtfixYtJSkoKaWpqIoQQVrUmhJDExETi6OhICgsLyenTp8m2bdvIt99+S8aNG0f27dvHemy/zbV161byzTffEH19ffL999+TsrIyUlpaKrJn06ZN5NtvvyWjRo0i33333VvHmSj5LV++nIwfP16k/F73bN68mbi4uJCxY8eS7du3s368lZaWkkmTJhEjIyNiampKli9fTvz8/IidnR2pqalh5XjVNXHiRMb19ddfk5s3bxJbW1vy4sULUlRURHJycljHZGxsTExNTcmXX35Jbt++TSwsLEh6ejohhLCu9+uub775hvj6+hI7OztSXV0tUm6v1mnp0qXk+vXrxN7enmRnZ7P2ENL8WHFwcCCEEMLn84mvry9ZtWoVsba2JlevXm2Vh8fjEW9vb7J8+XJibW1NLl68SDIyMljV+20uLy8vsmrVKjJ58mRy5MgRQghhHsuieHx9fcnKlStFzu1truvXr5Nly5YRS0tLcuzYMdaeuLg4Ym9vTwhpfl7Yt28fmTp1KrG1tSU//PADqaqqapVn7969xNLSklhaWpK1a9eSgoIC1n3uddeePXvI1KlTiYWFBVm+fDmprKwU2VNfX0/27t1LrKysiJ2dnUi5vc31008/EXNzc2Jra0u2b99O6uvrWXkSExPJrFmzyIULF8jYsWPJwYMHWT9Pvs01c+ZMxvXzzz+3eH6rra1lVfPXY9q3bx95+fIlaWhoILW1tSLH9Hp+ojxXvsuzf/9+1uPndc/MmTMJIYTcvn2brFq1itjb2xNbW1uybds21mPpba6VK1eSadOmEQsLC+Lm5kby8vJY1/tVz4oVK4i9vT0xNzcny5YtE2k8/Fd+33//PWvX6x5XV1dia2vLeEQZB8LelJmZSbKysoizszOZMGECGT16NAkMDGyVJzs7m8yZM4cYGRmRkSNHkps3b5K6ujpWr1Fe9wjjGTZsGDl//jwhhP1z5ofILSsri8yePZuMHz+ejBo1ity8eZO157+IiYkhx44dI46OjmT9+vWs3q+8j8bGRrJgwQJiZGTUqt9/+fIl2bx5M9m8eTMhhLB6v/I2Hj9+TH755Rdib29Ptm3bRkJCQlrlEXLlyhVia2tLLCwsyB9//CHy7wsEAhITE0OOHj1KZs2a1ep6vz4OBQJBq+otfI0rrPe2bdsIIa2vNyGExMbGkoMHDxIHB4c21/zy5ctM72Rb79drU1ZWRm7evEkOHDhAnJycyNy5c8m1a9daHdOHhJ6WSGkT+/fvx7lz5yApKQkVFRUoKChATk4O3bt3x4gRI8Dn81mfiLN//36cPXsWUlJSUFVVhby8PHNNUVER+vr6zKfKosQkLy8PeXl55oh74QqQ1uYnKyvL5NfQ0MAqP6FHSkqKiQlo3njX1NQUvXr1YjXDf/z4cRgYGGDWrFnMUvOIiAiYmZkhMzMTGzduZHWU8aueIUOGIC0tDVFRUTAzM8Pz589x8ODBFkfHiuJKT09HeHg4rKyskJ2djU2bNokck/B2v8jISCY3tp53xXT37l2Ym5sjJycHGzZsgIODw3s9p06dwogRI5g910JCQnDo0CHY2NjAy8sL2traLT5lE8UVFhaGw4cPw87ODj4+Phg8eDCrvX/e5jl06BBmzJiBO3fuQEtLq9UxCfOztrYWKb/XPeHh4fj1119ha2sLHx8faGhosDrZTl5eHv369YOmpiZ27NiB+vp6nDhxAtnZ2SgoKICUlBS0tbVZ5SYvLw8dHR3GxePx8McffyA7OxslJSXo3r07q0/4Xo+Jz+fj+PHjKCoqQnV1tcgxvZ7fyZMnkZ2djcLCQtaut8V06tQpPH/+HLW1tZCQkGAd019//YXhw4dDX18fXl5e8PLygo2NDYyNjXH9+nWMGjWK1SqLVz3Xr1/HzZs3mdWRPj4+MDMze2PDerauW7duwdraGmZmZggODsbIkSNZ7QH2uqe1ub3N5ePjg2nTpsHExATBwcEYMWIEK1dkZCSqq6thaWkJd3d3JCQk4Pz585g8eTL8/f0hLy/PrA4UxSNcWWpubo7g4GCoqqqy/iT8dVdycjLOnz8PCwsL3L17F3JyciLH5OHhgcTERFy4cAGmpqYi5fY2V1JSEi5evMjUSUZGhpXr77//xujRozFv3jzo6uoiKCgIlZWVzOmdovD3339DT0+PcYWEhLRwSUlJsdpo+/WYQkND8fLlS+jp6bFa4fwh8ntbTFVVVSJ7Tp06hcGDB2Ps2LG4d+8eYmNj4e7uzowBaWlp1vvSve6Ki4uDh4cHM8YVFRUxcuRIkT3x8fFwd3eHhYUFIiMjISUl1eqYXs3Pz8+PdX5vy+3q1aswNTXF7du3ISEhIVJMn3/+OczMzKCsrAx5eXmMGzcODg4OuHr1KoyMjFjdsve6R05ODuPGjYOjoyNu3LgBExMTVn33XfE4OzvDz88PhoaGrG/9+1C5CT3C3CZMmCDS7YiNjY0ICgrCzz//jGvXrqGhoQHa2tqwtLSEk5MTTE1NMWDAAJFd169fR11dHWRlZdG1a1eIi4tjyJAhGDt27Huf01/3CPfKNDY2hrGxMeTk5CAmJvbeO1Ze9Xh6eoLH40FLSwvW1taYPXs2s1pc1Nw8PT1RX18PBQUFGBoa4osvvoCtrS3Gjx8v8p1QYmJiUFNTw9ixYzFr1iyYmJhg4MCBIjmEHiHCrR6GDBkCPT09kfbiFBcXByEEsrKyGDhwIPT09KCsrAyBQCDy1kPk/1ZL9e7dG+PHj4ezszOMjIxEikeYjzC/YcOGYcaMGZg+fToMDAxYbckjEAgQGxuL06dPIy4uDiNHjsTw4cOhq6vL/O1EWenYntAN5SltwsfHB127dsWpU6ewYMECfP/998zmcnv27MHRo0dFcnXr1o1x/fDDD4iIiADQvNRTuImzKDEtXLgQ27dvZzbhO3z4sMgxcZHf22IS5rZnzx4cPnyYlSc9PR1DhgwB0NxM582bh9TUVOTn5+Pu3bvMNVE8YmJimDt3LuMJDw9n/aT8LtfTp0+Rn5+PiIgI1st6ucrtv/LLy8tDaGhoi02g/4vU1FSYmZkBaF4qvHHjRnTv3h39+/dH//79ERUVxTqm110bNmxAt27doKOjg/79+yMyMrJNMWlra0NHR4e1h8v8/is3HR0d3Lt3j3VMxsbGSEhIgIeHB+bOncu8mZSXl0dSUhJrz3+5ZGVlmQMiWuPR19fHnDlzICsry+owiQ+R37s8kpKSInn8/f2RlJSE5ORk+Pj4wMXFBba2tjAzM4OKigpzUq2onq+++go2NjYwMzNDly5dRNpn5W0uW1tb5naP1sbU2tz+K7/JkydDUVGR9UavwpMkhaceCSfse/fujUGDBiEmJqZVHuFt5b169cKgQYNYH+LyPlf//v1bHVNrc/uvmIQutqc9hYSEMK7Ro0fD0dERZ8+exeLFi5GZmck6nre5ZsyYgbNnz2LJkiUiud7lWbx4MZ49e9ammFqb33/FJIpn1KhRyMzMRFRUFM6dOwcnJycAYPbtSkhIaLVLuPdM7969MWDAANYnh73LIxzfbYmptfm9KyY1NTUMGjRIpOcVXV1dPH36FMXFxQCaTy/n8/nMCZPBwcGt9vB4PBgbG0MgELDu4e+Kx9DQEIQQ1vF86NyEt2sSQkTaYBtoPtzq9OnTcHR0xNixY3Hr1i2sXLkSGzZsQE5ODutbLl936evr4/bt21i5ciU2bdqE3NxcDB06lNVBLK97/P39sWrVKhw/fhx1dXUAwGpS41WPgYEBk9v69evblJuBgQH8/Pzw7bffYvPmzcjLy4OqqiqrmO7duwd3d/e3nj5I/m+fT7a8yyWMY+jQoUwvFMUjnEjS1NRkDipgG9errtcn+kTJ71XP63WVkZGBqqoq67+fj48PDh8+jC5duiA3NxcXLlyAuLg45OXlIRAIWO/H/FH4mMvGKJ822dnZZNOmTczXMTExZNu2bcTc3Jw4OzsTPT09Eh8fz4lr9OjRrFztGRNb1395nJycRIopISGBPH/+vMX3jh07Rnbs2EGcnZ1JUlJSu3o6e0yFhYXM/+fn57e4Nm/ePJKcnMw6Jq5cnT0mQppvjdq2bRvx9vYmpqamIt3++aFcnTWm5ORksmvXLmJmZkYMDQ1b3B45Z84ckpiY2K6ezh4TIYS59cvKyoq4uLiQqqoq8uLFC+Lg4CBSn+PK01lj4vF45NGjR4SQlrdYVFVVkV27dpF169axvv2LK1dnj+nFixfk22+/JQ4ODuTs2bPk8OHDzO/OnDlTpDHAlauzx1ReXk6++eYbYmVlRSwsLMiuXbuY5wJbW1vWry87mqejxkQIIfPnzyd37txp8b2MjAzy3XffMbektcWVmZlJ3NzcRHK9K6bVq1dz4uEqt9a4LC0tyahRo4itrS3ZsmULCQ0NZW5JDggIIDt27ODE5e/vz9rVXjGJ4uIqN0IIWbBgAbl//z4hhJBHjx4Re3t75tbIiIgIcvLkSdau9oZOblHaRENDw1v3wjly5AgxNzf/KK7OHpPwxadwz5mSkhJiZmZGpk2b9lE8nT2mtxEcHExmzJjRZg+Xrs4Sk3DvgqioKOLo6EhWrVpFCCGtmrjhytXZYxKSnp7OPG6ioqJaPQa48nTmmEpLS8nff/9NrK2tiZ6eHtm4cSM5evToR/N09piECB83ycnJIr3Q/5CuzhpTRUUFWbVqFTEyMiKzZs0iGzdubHU8XLk6a0wCgYDk5OSQx48fM/vERkVFkXnz5n3Sno4YU2NjIzlw4ACzf9jrzJkzhzx48KBdXR3Nw6WrrKyMLFiwgFRVVZGEhASyY8cOYmFhQezt7cnJkyfJrFmzyLlz51jFxJWrs8dUWFhIpk6d2mJv09OnT5Ply5cTQghxc3MTed/S9oROblE4QyAQME8Yv//+u0ib7H4oV2ePSdh4/v77b3LmzJmP7unsMRHS/Cl3SEgI8fHxaZOHS1dnjSkuLo48efKEEML+EIgP7ersMRHS/HgJCAho82ahXHk6e0xVVVUtVj9+bA+Xro4YE6X9aGhoIImJieTu3bsiHZrxIV2dPSYhT58+JdHR0Z3Ow6WrtZ64uDgyZcoUsmDBAuLn58d8v6SkhFhaWpK6urp2d3U0D1euqqoqEhgY+MYhV+Hh4cTFxYUMGzaM9QEjXLk6e0wFBQXkzJkzpKioiPney5cvyddff03CwsLI9OnTRRoH7Y0YIYR87FsjKZ2PoqIidOnSpcWm8B/b1dljIv+3CWFH8XDp6ogxUSgUCuXTpCM+p3T2mCiUzkR1dTXOnj2L6OhoPH/+HNra2lBVVYWysjJEPauNK1dH83DtIoSgqamJ2Tfq1q1buHHjBk6cOCGSh0tXZ42pqakJACAhIQEejwdpaWm4u7tj9+7dmDVrFrZu3SpSTO0JndyiUCgUCoVCoVAoFArlHfB4PIiJibXY4Lu8vBzFxcV49OgRxo8fD3V1dVabbXPl6mgermMC8M6fu3HjBjQ0NKCrq8sqJi5c/wsxiYuLv3Xj+by8PHz11Vdwc3NjDpHqiEhsF3XalEKhUCgUCoVCoVAolP8R9u/fj3PnzkFSUhIqKipQUFCAnJwcunfvjhEjRoDP50NJSaldXR3Nw3VM//77LyQlJaGqqtriLpeamhpoa2tDS0uLdUxcuP4XYjp79iykpKTecCkqKkJfXx9jx45l5fpY0JVbFAqFQqFQKBQKhUKhvAMjIyNMmDAB6enpqKurw5gxY2Bubg5jY2Ps2bMH9fX12LlzZ7u6OprnQ8VUX1/PeIyMjNoUU1tc/8sx/fTTT6irq2Pt+li8ueaMQqFQKBQKhUKhUCgUCnJycjBx4kTs2bMHABAbG4tr165h165d6Nq1K9LT0/HPP/+0q6ujedojpp07d3IWk6iu//WY0tLScPr0aVaujwlduUWhUCgUCoVCoVAoFMo74PF4aGxsfOMQqKNHj+LGjRvw9/dvd1dH89CYaEwfG7pyi0KhUCgUCoVCoVAolHcgLS3NbNr96ol0EhISsLe3/yiujuahMdGYPjZ05RaFQqFQKBQKhUKhUCgiUlRUhC5duryx2uVjujqah8ZEY2ov6OQWhUKhUCgUCoVCoVAoFArlk0X8YwdAoVAoFAqFQqFQKBQKhUKhtBY6uUWhUCgUCoVCoVAoFAqFQvlkoZNbFAqFQqFQ/ueYP38+3N3dOXFNnjwZUVFRnLj+i9zcXAwePBiNjY2sfj4/Px+6urpoamr6wJE1c+nSJfz444/t8m+1FTZ/fx6PBysrK5SXl7dTVBQKhUKhUFoLndyiUCgUCoXSoWmvyaNPndfr1KdPH8TGxkJCQuKD/9s8Hg/Hjx/H0qVLP/i/1V5IS0vD0dERf/zxx8cOhUKhUCgUynugk1sUCoVCoVAolDYRGBgIHR0d9OrV62OHwil2dna4du0aeDzexw6FQqFQKBTKf0AntygUCoVCoXyyXLlyBebm5hg7diyWLVuGoqIi5lpMTAwcHR2hp6cHR0dHxMTEvNVRXFwMOzs7nDp16q3Xs7OzsWDBAhgYGMDAwABr1qxBZWVli59JSUmBnZ0d9PT0sHr1ajQ0NDDXgoODMX36dOjr62P27Nl48uQJc+2PP/6AmZkZdHV1YW1tjYCAAOZaU1MT9u3bBwMDA0yZMgWhoaHvrMO6deuQn5+PZcuWQVdXF3/++ecbtzHOnz8fhw4dwuzZs6Grq4tly5bhxYsXWLNmDUaPHg1HR0fk5uYyzoyMDCxevBhjx46FpaUlbt269c5/PywsDGPGjGG+bmhowNq1a2FgYAB9fX04OjqitLQUAFBVVYXNmzfDyMgIxsbGOHToUItbJ69cuYKpU6cyNUlKSmLimT9/PvT19WFjY4PAwEDmdzZu3IgdO3bg66+/hq6uLmbNmoXs7GzmemRkJKysrKCnp4edO3fi1cPCs7KyMG/ePOjp6cHAwACrV69mrvXu3RvKysp4/PjxO3OnUCgUCoXy8aGTWxQKhUKhUD5J7t69i4MHD+Lw4cOIiIhA37594ebmBgCoqKiAi4sL5s+fj/v372Px4sVwcXHBixcvWjhycnIwf/58zJs375231BFC4OLigvDwcPj6+qKwsBBHjhxp8TO+vr44deoUAgMDkZqaCk9PTwBAcnIyNm/ejJ07d+L+/ftwdnbG8uXLmZVAGhoaOH/+PB49eoQVK1Zg3bp1KC4uBtA8yRMcHAwvLy9cvXoVt2/ffmctDhw4gD59+uDEiROIjY3FV1999dafu3XrFvbv34+wsDBkZ2dj9uzZcHR0RHR0NPr3749jx44BAGpra7FkyRLY2toiKioKhw4dwo4dO5Cenv5W79OnT9GvXz/m62vXrqG6uhohISG4f/8+duzYAVlZWQDNE1GSkpLw9/eHl5cXIiMjmf2vfH19ceTIEezbtw8xMTE4fvw4VFRUwOfzsWzZMhgaGiIqKgpbt27F2rVrkZmZ2SK3FStW4MGDB9DU1MShQ4cAAOXl5VixYgVWr16Ne/fuQVNTs8VE56+//gpDQ0M8ePAAYWFhmDdvXovcdHR0WkxIUigUCoVC6XjQyS0KhUKhUCifJN7e3nB0dMSwYcMgLS0NNzc3PH78GLm5uQgJCYGWlhbs7e0hKSkJW1tb6OjoIDg4mPn99PR0LFy4EK6urnB2dn7nv6OlpQVDQ0NIS0uja9euWLx4MR48eNDiZ+bPn49evXpBRUUFpqamSElJAQBcvnwZzs7OGDlyJCQkJODg4AApKSlmJdDUqVPRq1cviIuLw9raGlpaWoiPjwfQPNGzcOFCqKmpQUVFBS4uLm2u2YwZM6CpqYkuXbpg4sSJ0NDQwIQJEyApKQkrKyskJycDAEJCQtC3b184OjpCUlISn332GSwtLd85wVZVVQUFBQXma0lJSVRUVCArKwsSEhIYPnw4FBUVUVpaitDQUGzevBny8vLo1q0bFi1aBB8fHwCAh4cHli5dihEjRkBMTAxaWlro27cv4uLiUFtbi6+//hrS0tIYP348TE1Nmd8DADMzM4wYMQKSkpKYNm0a8zcICwvDwIEDYWVlBSkpKSxcuBDdu3dvEWt+fj6Ki4shIyMDfX39FrkpKCi8sVKPQqFQKBRKx0LyYwdAoVAoFAqF0hqKi4sxbNgw5msFBQWoqKigqKgIxcXF6NOnT4uf79OnT4vbFr29vaGpqQlLS0vmew8fPmRWPfXp0wc+Pj4oLS3Fjz/+iIcPH6KmpgaEECgpKbVw9+jRg/l/OTk5ZvVVfn4+vLy88O+//zLX+Xw+c93Lywv//PMP8vLyADSvmBKuLisuLoaamlqL+NvKq5M6MjIyLb6WlZVFbW0tACAvLw/x8fEtJnqampowbdq0t3qVlJRQU1PDfD19+nQUFhbCzc0NlZWVmDZtGr777jvk5+ejsbERRkZGzM8KBAImz4KCAmhqar7hLy4uRu/evSEu/v8/l3397/muXIS/K0RMTKxFXdetW4dff/0VM2fOhLKyMhYvXoyZM2cy12tqat74e1MoFAqFQulY0MktCoVCoVAonyQ9e/ZkJoWA5omhiooK9OrVCz179kR+fn6Lny8oKICxsTHz9YoVKxAeHo41a9bg0KFDkJCQgL6+PmJjY1v83i+//AIxMTF4e3tDRUUFd+7cwc6dO1nFqKamhmXLluGbb75541peXh62bt2K06dPQ1dXFxISEpg+fTpzvUePHigoKGgRf3uhpqaGMWPG4J9//mH184MHD8bz58+Zr6WkpLBixQqsWLECubm5+Prrr9GvXz9MmjQJ0tLSuHfvHiQl33wZqqam1mKvLCE9e/ZEYWEhBAIBM8FVUFAAbW3t98bWo0cPFBYWMl8TQlrUskePHti9ezeA5snNxYsXY8yYMdDS0gIAZGZmYsmSJazqQKFQKBQK5eNAb0ukUCgUCoXS4eHz+WhoaGD+a2xs/H/t3Uso9Hscx/HPPDFJJJesWLE1uY0Ro2GjTHIpZG0xkdvOwqywkVCiTHIpUixIKQsLyQo7l8g1TIqwmMKUYeYsns6/85wc9Jzz9Jyp96v+u//v//v+fstP/9/3p/Lyci0uLurw8FAvLy8aHByUxWJRSkqKHA6HLi4utLy8rNfXV62srOj09FTFxcXGNyMjIzU0NCS/36+Ojg4Fg8F35356elJ0dLRiY2N1e3v7j43n31NbW6u5uTnt7OwoFArp+flZ6+vrenx8lN/vl8lkUkJCgiRpYWFBJycnxtiysjLNzMzo5uZGPp9PY2NjH86VlJQkr9f75do+UlxcrIuLCy0tLSkQCCgQCGh3d1dnZ2fvvu9wOH44qrm5uamjoyO9vb0pJiZGERER+vbtm5KTk1VYWKje3l49Pj4qGAzq6upK29vbkqSamhpNTk5qf39foVBIl5eXur6+lsViUVRUlMbHxxUIBLS1taW1tTU5nc5P1+JwOHRycqLV1VW9vr5qenraaG4vyeijJklxcXEymUxGgHZ7eyufz6fMzMyf3ksAAPDrEW4BAID/PZfLJYvFYjzDw8MqKChQe3u7WltbZbfb5fV6jSbi8fHx8ng8mpqaks1m0/gxU0wbAAABqklEQVT4uDwejxEk/clsNmtkZEQPDw/q7Ox8N+BqaWnRwcGBcnNz5XK5VFpa+uW6MzIy1NPTo+7ublmtVpWWlhrN5tPT09XQ0KD6+noVFBTo+PhY2dnZxti6ujrZ7XZVVlaqurr603ldLpdGR0eVm5uriYmJL9f4npiYGE1MTGhlZUVFRUWy2+3q7+83GuH/XUlJic7Pz41jgvf392pra1NOTo6cTqfy8vKMv9L6+voUCATkdDpltVrV1tamu7s7Sd8DvcbGRuMGx+bmZvl8PpnNZnk8Hm1sbCg/P19dXV3q6+tTWlrap2tJSEjQ0NCQBgYGZLPZdHl5+cM+7+3tqba2VllZWWpqapLb7VZqaqqk70dXq6qqZDab/9V+AgCAX8sU+utdyAAAAMBPmJ+f1+npqdxu9+8u5T/x8vKiiooKzc7OKjEx8XeXAwAAPkC4BQAAAAAAgLDFsUQAAAAAAACELcItAAAAAAAAhC3CLQAAAAAAAIQtwi0AAAAAAACELcItAAAAAAAAhC3CLQAAAAAAAIQtwi0AAAAAAACELcItAAAAAAAAhK0/AEcSJHWsAm3JAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = range(len(box_data_2))\n",
    "plt.figure(figsize=(20,8))\n",
    "plt.boxplot(box_data_2, showfliers=False, patch_artist=True, whis=[10,90])\n",
    "# plt.hlines(9260, 0, 1200, colors='r', linestyles='dashed', label='IPZ limit')\n",
    "# plt.hlines(-9260, 0, 1200, colors='r', linestyles='dashed')\n",
    "# plt.hlines(-9260, 0, 1200, colors='r', linestyles='dashed', label='IPZ limit')\n",
    "plt.xticks(x, [i[0] for i in box_data_sort])\n",
    "plt.xticks(rotation=70)\n",
    "plt.xlabel('Look-ahead time (seconds)')\n",
    "plt.ylabel('CTE in meters')\n",
    "plt.title('Evolution of CTE over look-ahead time')\n",
    "# plt.legend(prop={'size': 16})\n",
    "# plt.ylim((-100000,100000))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No handles with labels found to put in legend.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create bin dataframe\n",
    "box_data = []\n",
    "bin_df = bin_dp_df\n",
    "\n",
    "for k in bin_df.keys():\n",
    "    if '_cte' in k:\n",
    "        box_data.extend([i for i in bin_df[k] if not np.isnan(i)])\n",
    "\n",
    "from matplotlib import mlab\n",
    "fig, ax = plt.subplots(figsize=(15, 10))\n",
    "range_lim = 100000\n",
    "\n",
    "box_data = [x for x in box_data if abs(x) < range_lim]\n",
    "\n",
    "n_bins = 200\n",
    "\n",
    "# plot the cumulative histogram\n",
    "n, bins, patches = ax.hist(box_data, n_bins, normed=0, histtype='stepfilled',\n",
    "                           cumulative=False, alpha=0.6)\n",
    "    \n",
    "#     plt.xlabel('')\n",
    "# plt.legend(prop={'size': 14})\n",
    "plt.xlim(-range_lim,range_lim)\n",
    "# plt.ylim(0,100000)\n",
    "plt.xlabel('CTE')\n",
    "plt.ylabel('Count')\n",
    "plt.title('CTE for M3 and ADSB flight segments')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DescribeResult(nobs=51419, minmax=(-99966.96675904862, 99964.56601435547), mean=-759.7829257100001, variance=285410255.62557226, skewness=-0.618377349954631, kurtosis=12.049504589513662)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy import stats\n",
    "\n",
    "stats.describe(box_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2160x2160 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "try:\n",
    "    conn = psql.connect(\"dbname='thesisdata' user='postgres' host='localhost' password='postgres'\")\n",
    "except Exception as e:\n",
    "    print(\"Unable to connect to the database.\")\n",
    "    print(e)\n",
    "\n",
    "max_inserts = 100\n",
    "fetch_batch_size = max_inserts\n",
    "cnt = 0\n",
    "\n",
    "cur_read = conn.cursor(cursor_factory=RealDictCursor)\n",
    "\n",
    "cur_read.execute(\"select t1.callsign, t1.ep_seg_b, t1.lat_seg_b, t1.lon_seg_b, t2.ts, t2.lat, t2.lon, t2.hdg \\\n",
    "                from public.ddr2_flights as t1 inner join public.adsb_flights as t2 \\\n",
    "                on t1.callsign = t2.callsign and abs(t1.start_ep - t2.start_ep) < 6000 limit 10;\")\n",
    "\n",
    "\n",
    "proj_dct = {}\n",
    "plt.figure(figsize=(30,30))\n",
    "bin_cte_hdg = []\n",
    "\n",
    "for x in cur_read.fetchall():\n",
    "    dc = {k: x[k] for k in ['ep_seg_b','lat_seg_b', 'lon_seg_b']}\n",
    "    ac = {k: x[k] for k in ['ts','lat','lon', 'hdg']}\n",
    "    \n",
    "    dc = pd.DataFrame.from_dict(dc)\n",
    "    ac = pd.DataFrame.from_dict(ac)\n",
    "\n",
    "    dc['wps'] = list(zip(dc.lat_seg_b, dc.lon_seg_b))\n",
    "    try:\n",
    "        df = add_waypoints_free(ac, dc['wps'])\n",
    "    except Exception as e:\n",
    "        print(e)\n",
    "        continue\n",
    "\n",
    "    df[['curr_lat', 'curr_lon']] = df['curr_wp'].apply(pd.Series)\n",
    "    df[['next_lat', 'next_lon']] = df['next_wp'].apply(pd.Series)\n",
    "    df[['last_lat', 'last_lon']] = df['last_wp'].apply(pd.Series)\n",
    "    \n",
    "    hdg_ac_arr = []\n",
    "    hdg_route_arr = []\n",
    "    hdg_diff_arr = []\n",
    "\n",
    "    fl_dd = pd.DataFrame()\n",
    "\n",
    "    for ii, r in df.iterrows():\n",
    "\n",
    "        route_hdg = calc_compass_bearing(r['last_wp'], r['curr_wp'])\n",
    "        hdg_ac_arr.append(r['hdg'])\n",
    "        hdg_route_arr.append(route_hdg)\n",
    "        hdg_diff_arr.append(route_hdg - r['hdg'])\n",
    "\n",
    "    fl_dd['hdg_ac'] = hdg_ac_arr\n",
    "    fl_dd['hdg_ac'] = fl_dd['hdg_ac'].fillna(method='ffill')\n",
    "    fl_dd['hdg_route'] = hdg_route_arr\n",
    "    fl_dd['time_proj'] = df['ts'] - df['ts'].min()\n",
    "    \n",
    "    plt.scatter(fl_dd['hdg_route'],fl_dd['hdg_ac'],s=2, c='b')\n",
    "    plt.scatter(fl_dd['hdg_route'],fl_dd['hdg_route'],s=2, c='r')\n",
    "    plt.plot(fl_dd['time_proj'], fl_dd['hdg_route']-fl_dd['hdg_ac'])\n",
    "    \n",
    "    bin_cte_hdg.extend(hdg_diff_arr)\n",
    "    \n",
    "plt.show()\n",
    "    \n",
    "#     plt.figure(figsize=(30,30))\n",
    "#     plt.scatter(df['curr_lon'],df['curr_lat'],s=2, c='b')\n",
    "#     plt.scatter(df['lon'],df['lat'],s=2, c='r')\n",
    "#     plt.show()\n",
    "    \n",
    "#     plt.figure(figsize=(30,30))\n",
    "#     plt.plot(fl_dd['hdg_route'],'-b')\n",
    "#     plt.plot(fl_dd['hdg_ac'], '-r')\n",
    "#     plt.show()\n",
    "#     bin_cte.extend(cte_arr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "bin_cte = pd.Series(bin_cte)\n",
    "bin_cte.plot.hist(bins=500,figsize=(20,10),xlim=(-60000,60000),alpha = 0.6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "bin_cte_hdg = pd.Series(bin_cte_hdg)\n",
    "bin_cte_hdg.plot.hist(bins=100,figsize=(20,10),alpha=0.7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "plt.figure(figsize=(20,20))\n",
    "for i, r in df.iterrows(): \n",
    "    plt.plot([r['curr_lat'],r['lat']],[r['curr_lon'],r['lon']], 'r--')\n",
    "    plt.plot([r['next_lat'],r['lat']],[r['next_lon'],r['lon']], 'k--')\n",
    "\n",
    "for i, r in df.iterrows(): \n",
    "    plt.scatter(r['lat'],r['lon'],c='b',marker='x')\n",
    "    plt.scatter(r['curr_lat'],r['curr_lon'],c='g',marker='x')\n",
    "    \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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